Ricardo Henao

Biostatistics & Bioinformatics, Division of Translational Biomedical

Associate Professor of Biostatistics & Bioinformatics

Ricardo Henao Profile Photo

Education

Ph.D. Technical University of Denmark (Denmark), 2011

Positions

Associate Professor of Biostatistics & Bioinformatics
Assistant Professor in the Department of Electrical and Computer Engineering
Member in the Duke Clinical Research Institute
Member of Duke Center for Applied Genomics and Precision Medicine

Courses Taught

IDS 793: Independent Study
EGR 393: Research Projects in Engineering
ECE 899: Special Readings in Electrical Engineering
ECE 891: Internship
ECE 494: Projects in Electrical and Computer Engineering
ECE 493: Projects in Electrical and Computer Engineering
ECE 392: Projects in Electrical and Computer Engineering

Publications

Huang WA, Engelhard M, Coffman M, Hill ED, Weng Q, Scheer A, et al. A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis. J Biomed Inform. 2024 Sep;157:104711.
Jeong HK, Park C, Jiang SW, Nicholas M, Chen S, Henao R, et al. Image Quality Assessment Using Convolutional Neural Network in Clinical Skin Images. JID Innov. 2024 Jul;4(4):100285.
Wang AT, Henao R, Carin L. Transformer In-Context Learning for Categorical Data. 2024.
Ashhad M, Henao R. Conditioning on Time is All You Need for Synthetic Survival Data Generation. 2024.
Zhang H, Cong Y, Wang Z, Zhang L, Zhao M, Chen L, et al. Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2. IEEE Trans Neural Netw Learn Syst. 2024 May;35(5):6558–69.
Chu Y, Luo G, Zhou L, Cao S, Ma G, Meng X, et al. Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy. 2024.
Assaad S, Dov D, Park C, Davis R, Kovalsky SZ, Lee WT, et al. A Preliminary Study Comparing the Performance of Thyroid Molecular Tests to a Deep Learning Algorithm in Predicting Malignancy in Indeterminate Thyroid Fine Needle Aspiration Biopsies. Thyroid. 2024 Apr;34(4):531–5.
Economou-Zavlanos NJ, Bessias S, Cary MP, Bedoya AD, Goldstein BA, Jelovsek JE, et al. Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J Am Med Inform Assoc. 2024 Feb 16;31(3):705–13.
Hong C, Liu M, Wojdyla DM, Hickey J, Pencina M, Henao R. Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. J Biomed Inform. 2024 Jan;149:104532.
Steinbrink JM, Liu Y, Henao R, Tsalik EL, Ginsburg GS, Ramsburg E, et al. 305. PBMC-Derived Transcriptomic Signatures Accurately Discriminate Between Viral, Bacterial, and Fungal Infections and can be Translated to Real-World Human Infections. Open Forum Infectious Diseases. 2023 Nov 27;10(Supplement_2).
Dow ER, Jeong HK, Katz EA, Toth CA, Wang D, Lee T, et al. A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography. JAMA Ophthalmol. 2023 Nov 1;141(11):1052–61.
Mallya P, Stevens LM, Zhao J, Hong C, Henao R, Economou-Zavlanos N, et al. Facilitating Harmonization of Variables in Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository. Circ Cardiovasc Qual Outcomes. 2023 Nov;16(11):e009938.
Pavon JM, Previll L, Woo M, Henao R, Solomon M, Rogers U, et al. Machine learning functional impairment classification with electronic health record data. J Am Geriatr Soc. 2023 Sep;71(9):2822–33.
Dov D, Elliott Range D, Cohen J, Bell J, Rocke DJ, Kahmke RR, et al. Deep-Learning-Based Screening and Ancillary Testing for Thyroid Cytopathology. Am J Pathol. 2023 Sep;193(9):1185–94.
Kong F, Li Y, Nassif H, Fiez T, Henao R, Chakrabarti S. Neural Insights for Digital Marketing Content Design. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2023. p. 4320–32.
Zhang H, Wang C, Wang Z, Duan Z, Chen B, Zhou M, et al. Learning Hierarchical Document Graphs From Multilevel Sentence Relations. IEEE Trans Neural Netw Learn Syst. 2023 Aug;34(8):4273–85.
Wegermann K, Fudim M, Henao R, Howe CF, McGarrah R, Guy C, et al. Serum Metabolites Are Associated With HFpEF in Biopsy-Proven Nonalcoholic Fatty Liver Disease. J Am Heart Assoc. 2023 Jul 18;12(14):e029873.
Tran BV, Moris D, Markovic D, Zaribafzadeh H, Henao R, Lai Q, et al. Development and validation of a REcurrent Liver cAncer Prediction ScorE (RELAPSE) following liver transplantation in patients with hepatocellular carcinoma: Analysis of the US Multicenter HCC Transplant Consortium. Liver Transpl. 2023 Jul 1;29(7):683–97.
Wu J, Wang R, Zhao H, Zhang R, Lu C, Li S, et al. Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023. 2023 Jun 27;37:4729–37.
Wu J, Yu T, Wang R, Song Z, Zhang R, Zhao H, et al. InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. 2023.
Qi S-A, Kumar N, Farrokh M, Sun W, Kuan L-H, Ranganath R, et al. An Effective Meaningful Way to Evaluate Survival Models. 2023.
Assaad S, Dov D, Davis R, Kovalsky S, Lee WT, Kahmke R, et al. Thyroid Cytopathology Cancer Diagnosis from Smartphone Images Using Machine Learning. Mod Pathol. 2023 Jun;36(6):100129.
Kong F, Yuan S, Hao W, Henao R. Mitigating Test-Time Bias for Fair Image Retrieval. 2023.
Chapfuwa P, Tao C, Li C, Khan I, Chandross KJ, Pencina MJ, et al. Calibration and Uncertainty in Neural Time-to-Event Modeling. IEEE Trans Neural Netw Learn Syst. 2023 Apr;34(4):1666–80.
Bai K, Wang G, Li J, Park S, Lee S, Xu P, et al. Open World Classification with Adaptive Negative Samples. 2023.
Wang R, Cheng P, Henao R. Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. 2023.
Kong F, Li Y, Nassif H, Fiez T, Henao R, Chakrabarti S. Neural Insights for Digital Marketing Content Design. 2023.
Wang R, Yu T, Wu J, Zhao H, Kim S, Zhang R, et al. Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets. In: Proceedings of the Annual Meeting of the Association for Computational Linguistics. 2023. p. 7449–63.
Jeong HK, Park C, Henao R, Kheterpal M. Deep Learning in Dermatology: A Systematic Review of Current Approaches, Outcomes, and Limitations. JID Innov. 2023 Jan;3(1):100150.
Verma VK, Mehta N, Si S, Henao R, Carin L. Pushing the Efficiency Limit Using Structured Sparse Convolutions. In: Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023. 2023. p. 6492–502.
Moris D, Henao R, Hensman H, Stempora L, Chasse S, Schobel S, et al. Multidimensional machine learning models predicting outcomes after trauma. Surgery. 2022 Dec;172(6):1851–9.
Verma VK, Mehta N, Si S, Henao R, Carin L. Pushing the Efficiency Limit Using Structured Sparse Convolutions. 2022.
Wang S, Choi Y, Chen J, El-Khamy M, Henao R. Toward Sustainable Continual Learning: Detection and Knowledge Repurposing of Similar Tasks. 2022.
Bai K, Zhang A, Li Z, Heano R, Wang C, Carin L. Collaborative Anomaly Detection. 2022.
Yang T, Henao R. TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile. PLoS Comput Biol. 2022 Sep;18(9):e1009921.
Dov D, Kovalsky SZ, Feng Q, Assaad S, Cohen J, Bell J, et al. Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images. Arch Pathol Lab Med. 2022 Jul 1;146(7):872–8.
Eckhoff AM, Connor AA, Thacker JKM, Blazer DG, Moore HG, Scheri RP, et al. A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery. Ann Surg. 2022 Jun 1;275(6):1094–102.
Park C, Jeong HK, Henao R, Kheterpal M. Current Landscape of Generative Adversarial Networks for Facial Deidentification in Dermatology: Systematic Review and Evaluation. JMIR Dermatology. 2022 May 1;5(2).
Draelos RL, Ezekian JE, Zhuang F, Moya-Mendez ME, Zhang Z, Rosamilia MB, et al. GENESIS: Gene-Specific Machine Learning Models for Variants of Uncertain Significance Found in Catecholaminergic Polymorphic Ventricular Tachycardia and Long QT Syndrome-Associated Genes. Circ Arrhythm Electrophysiol. 2022 Apr;15(4):e010326.
Wisely CE, Wang D, Henao R, Grewal DS, Thompson AC, Robbins CB, et al. Convolutional neural network to identify symptomatic Alzheimer's disease using multimodal retinal imaging. Br J Ophthalmol. 2022 Mar;106(3):388–95.
Chapfuwa P, Rose S, Carin L, Meeds E, Henao R. Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations. 2022.
Isik YA, Davis C, Chapfuwa P, Henao R. Flexible Triggering Kernels for Hawkes Process Modeling. 2022.
Yang T, Henao R. TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile. bioRxiv. 2022.
Jeong HK, Park C, Henao R, Kheterpal M. Privacy Protection With Facial Deidentification Machine Learning Methods: Can Current Methods Be Applied to Dermatology? Iproceedings. 2021 Dec 17;6(1):e35431–e35431.
Park C, Jeong HK, Henao R, Kheterpal M. Current Landscape of Generative Adversarial Networks for Facial Deidentification in Dermatology: Systematic Review and Evaluation (Preprint). JMIR Publications Inc. 2021.
Jeong HK, Park C, Henao R, Kheterpal M. Privacy Protection With Facial Deidentification Machine Learning Methods: Can Current Methods Be Applied to Dermatology? (Preprint). 2021 Dec 3;
Pagidipati NJ, Phelan M, Page C, Clowse M, Henao R, Peterson ED, et al. The importance of weight stabilization amongst those with overweight or obesity: Results from a large health care system. Prev Med Rep. 2021 Dec;24:101615.
Tsalik EL, Henao R, Montgomery JL, Nawrocki JW, Aydin M, Lydon EC, et al. Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test. Crit Care Med. 2021 Oct 1;49(10):1651–63.
Van Neste L, Wojno KJ, Henao R, Mane S, Korman H, Hafron J, et al. Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer. Cells. 2021 Sep 28;10(10).
Markwalter CF, Nyunt MH, Han ZY, Henao R, Jain A, Taghavian O, et al. Antibody signatures of asymptomatic Plasmodium falciparum malaria infections measured from dried blood spots. Malar J. 2021 Sep 23;20(1):378.
Alexopoulos A-S, Crowley MJ, Wang Y, Moylan CA, Guy CD, Henao R, et al. Glycemic Control Predicts Severity of Hepatocyte Ballooning and Hepatic Fibrosis in Nonalcoholic Fatty Liver Disease. Hepatology. 2021 Sep;74(3):1220–33.
Grzesiak E, Bent B, McClain MT, Woods CW, Tsalik EL, Nicholson BP, et al. Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset. JAMA Netw Open. 2021 Sep 1;4(9):e2128534.
Mahle RE, Suchindran S, Henao R, Steinbrink JM, Burke TW, McClain MT, et al. Validation of a Host Gene Expression Test for Bacterial/Viral Discrimination in Immunocompromised Hosts. Clin Infect Dis. 2021 Aug 16;73(4):605–13.
She X, Zhai Y, Henao R, Woods CW, Chiu C, Ginsburg GS, et al. Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes. IEEE Trans Biomed Eng. 2021 Aug;68(8):2377–88.
Garside N, Zaribafzadeh H, Henao R, Chung R, Buckland D. CPT to RVU conversion improves model performance in the prediction of surgical case length. Sci Rep. 2021 Jul 8;11(1):14169.
Gao Q, Wang D, Amason JD, Yuan S, Tao C, Henao R, et al. Gradient Importance Learning for Incomplete Observations. 2021 Jul 5;
Steinbrink JM, Myers RA, Hua K, Johnson MD, Seidelman JL, Tsalik EL, et al. The host transcriptional response to Candidemia is dominated by neutrophil activation and heme biosynthesis and supports novel diagnostic approaches. Genome Med. 2021 Jul 5;13(1):108.
Kong F, Henao R. Efficient Classification of Very Large Images with Tiny Objects. 2021 Jun 4;
Xiu Z, Tao C, Gao M, Davis C, Goldstein BA, Henao R. Variational Disentanglement for Rare Event Modeling. Proc AAAI Conf Artif Intell. 2021 May 18;35(12):10469–77.
Wang L, Balmat TJ, Antonia AL, Constantine FJ, Henao R, Burke TW, et al. An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility. Genome Med. 2021 May 17;13(1):83.
Chapfuwa P, Assaad S, Zeng S, Pencina MJ, Carin L, Henao R. Enabling counterfactual survival analysis with balanced representations. In: ACM CHIL 2021 - Proceedings of the 2021 ACM Conference on Health, Inference, and Learning. 2021. p. 133–45.
Dov D, Assaad S, Si S, Wang R, Xu H, Kovalsky SZ, et al. Affinitention nets: Kernel perspective on attention architectures for set classification with applications to medical text and images. In: ACM CHIL 2021 - Proceedings of the 2021 ACM Conference on Health, Inference, and Learning. 2021. p. 14–24.
Xia M, Kheterpal MK, Wong SC, Park C, Ratliff W, Carin L, et al. Malignancy Prediction and Lesion Identification from Clinical Dermatological Images. 2021 Apr 2;
Wegermann K, Howe C, Henao R, Wang Y, Guy CD, Abdelmalek MF, et al. Serum Bile Acid, Vitamin E, and Serotonin Metabolites Are Associated With Future Liver-Related Events in Nonalcoholic Fatty Liver Disease. Hepatol Commun. 2021 Apr;5(4):608–17.
McClain MT, Constantine FJ, Nicholson BP, Nichols M, Burke TW, Henao R, et al. A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study. Lancet Infect Dis. 2021 Mar;21(3):396–404.
McClain MT, Constantine FJ, Henao R, Liu Y, Tsalik EL, Burke TW, et al. Dysregulated transcriptional responses to SARS-CoV-2 in the periphery. Nat Commun. 2021 Feb 17;12(1):1079.
Kong F, Liu X-Y, Henao R. Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification. 2021.
Wosik J, Clowse MEB, Overton R, Adagarla B, Economou-Zavlanos N, Cavalier J, et al. Impact of the COVID-19 pandemic on patterns of outpatient cardiovascular care. Am Heart J. 2021 Jan;231:1–5.
Turpin M, Watson J, Engelhard M, Henao R, Thompson D, Carin L, et al. Machine Learning Prediction of Surgical Intervention for Small Bowel Obstruction. 2021;
Subramanian V, Engelhard M, Berchuck S, Chen L, Henao R, Carin L. SpanPredict: Extraction of Predictive Document Spans with Neural Attention. In: NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2021. p. 5234–58.
Dov D, Kovalsky SZ, Assaad S, Cohen J, Range DE, Pendse AA, et al. Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Medical Image Anal. 2021;67:101814–101814.
Draelos RL, Dov D, Mazurowski MA, Lo JY, Henao R, Rubin GD, et al. Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Medical Image Anal. 2021;67:101857–101857.
Dov D, Kovalsky SZ, Assaad S, Cohen J, Range DE, Pendse AA, et al. Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Med Image Anal. 2021 Jan;67:101814.
Ross M, Henao R, Burke TW, Ko ER, McClain MT, Ginsburg GS, et al. A comparison of host response strategies to distinguish bacterial and viral infection. PLoS One. 2021;16(12):e0261385.
Assaad S, Zeng S, Mehta N, Henao R, Tao C, Datta S, et al. Counterfactual Representation Learning with Balancing Weights. Proceedings of Machine Learning Research. 2021 Jan 1;130:1972–80.
Assaad S, Zeng S, Tao C, Datta S, Mehta N, Henao R, et al. Counterfactual Representation Learning with Balancing Weights. In: Banerjee A, Fukumizu K, editors. AISTATS. PMLR; 2021. p. 1972–80.
Chen L, Wang D, Gan Z, Liu J, Henao R, Carin L. Wasserstein contrastive representation distillation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2021 Jan 1;16291–300.
Draelos RL, Dov D, Mazurowski MA, Lo JY, Henao R, Rubin GD, et al. Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Med Image Anal. 2021 Jan;67:101857.
Kong F, Liu X-Y, Henao R. Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification. CoRR. 2021;abs/2101.03154.
Wang L, Balmat TJ, Antonia AL, Constantine FJ, Henao R, Burke TW, et al. An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility. medRxiv. 2020 Dec 22;
Giroux NS, Ding S, McClain MT, Burke TW, Petzold E, Chung HA, et al. Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity. bioRxiv. 2020 Dec 9;
Xiu Z, Tao C, Gao M, Davis C, Goldstein B, Henao R. Variational Disentanglement for Rare Event Modeling. In: ArXiv. 2020.
Abdulrahim JW, Kwee LC, Alenezi F, Sun AY, Baras A, Ajayi TA, et al. Identification of Undetected Monogenic Cardiovascular Disorders. J Am Coll Cardiol. 2020 Aug 18;76(7):797–808.
Liu Y, Tsalik EL, Jiang Y, Ko ER, Woods CW, Henao R, et al. Average Weighted Accuracy: Pragmatic Analysis for a Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) Study. Clin Infect Dis. 2020 Jun 10;70(12):2736–42.
Tillekeratne LG, Suchindran S, Ko ER, Petzold EA, Bodinayake CK, Nagahawatte A, et al. Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population. Open Forum Infect Dis. 2020 Jun;7(6):ofaa194.
Engelhard M, Berchuck S, D’Arcy J, Henao R. Neural Conditional Event Time Models. 2020 Apr 3;
Xiu Z, Tao C, Henao R. Variational Learning of Individual Survival Distributions. Proc ACM Conf Health Inference Learn (2020). 2020 Apr;2020:10–8.
Elliott Range DD, Dov D, Kovalsky SZ, Henao R, Carin L, Cohen J. Application of a machine learning algorithm to predict malignancy in thyroid cytopathology. Cancer Cytopathol. 2020 Apr;128(4):287–95.
Chapfuwa P, Li C, Mehta N, Carin L, Henao R. Survival cluster analysis. ACM CHIL 2020 - Proceedings of the 2020 ACM Conference on Health, Inference, and Learning. 2020 Feb 4;60–8.
Wang D, Yang Y, Tao C, Kong F, Henao R, Carin L. Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. CoRR. 2020;abs/2012.03369.
Engelhard M, Berchuck S, D’Arcy J, Henao R. Neural Conditional Event Time Models. In: Proceedings of Machine Learning Research. 2020. p. 223–44.
Du K, Chitneni SK, Suzuki A, Wang Y, Henao R, Hyun J, et al. Increased Glutaminolysis Marks Active Scarring in Nonalcoholic Steatohepatitis Progression. Cell Mol Gastroenterol Hepatol. 2020;10(1):1–21.
Xu H, Luo D, Henao R, Shah S, Carin L. Learning Autoencoders with Relational Regularization. In: ICML. PMLR; 2020. p. 10576–86.
Yuan S, Bai K, Chen L, Zhang Y, Tao C, Li C, et al. Advancing weakly supervised cross-domain alignment with optimal transport. In: BMVC. BMVA Press; 2020.
Wang R, Si S, Wang G, Zhang L, Carin L, Henao R. Integrating task specific information into pretrained language models for low resource fine tuning. In: Findings of the Association for Computational Linguistics Findings of ACL: EMNLP 2020. 2020. p. 3181–6.
Xu H, Luo D, Henao R, Shah S, Carin L. Learning autoencoders with relational regularization. 37th International Conference on Machine Learning, ICML 2020. 2020 Jan 1;PartF168147-14:10507–17.
Xiu Z, Tao C, Henao R. Variational learning of individual survival distributions. In: Ghassemi M, editor. CHIL. ACM; 2020. p. 10–8.
Yuan S, Bai K, Chen L, Zhang Y, Tao C, Li C, et al. Weakly supervised cross-domain alignment with optimal transport. 31st British Machine Vision Conference, BMVC 2020. 2020 Jan 1;
Chapfuwa P, Li C, Mehta N, Carin L, Henao R. Survival cluster analysis. In: Ghassemi M, editor. CHIL. ACM; 2020. p. 60–8.
Si S, Wang R, Wosik J, Zhang H, Dov D, Wang G, et al. Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message Triage. Proceedings of Machine Learning Research. 2020 Jan 1;126:436–56.
Chapfuwa P, Assaad S, Zeng S, Pencina MJ, Carin L, Henao R. Survival Analysis meets Counterfactual Inference. CoRR. 2020;abs/2006.07756.
Chen L, Bai K, Tao C, Zhang Y, Wang G, Wang W, et al. Sequence generation with optimal-transport-enhanced reinforcement learning. In: AAAI 2020 - 34th AAAI Conference on Artificial Intelligence. 2020. p. 7512–20.
Chen J, Xiu Z, Goldstein BA, Henao R, Carin L, Tao C. Supercharging Imbalanced Data Learning With Causal Representation Transfer. CoRR. 2020;abs/2011.12454.
Lorenzi E, Henao R, Heller K. Hierarchical infinite factor models for improving the prediction of surgical complications for geriatric patients. Annals of Applied Statistics. 2019 Dec 1;13(4):2637–61.
Lydon EC, Henao R, Burke TW, Aydin M, Nicholson BP, Glickman SW, et al. Validation of a host response test to distinguish bacterial and viral respiratory infection. EBioMedicine. 2019 Oct;48:453–61.
Engelhard MM, Oliver JA, Henao R, Hallyburton M, Carin LE, Conklin C, et al. Identifying Smoking Environments From Images of Daily Life With Deep Learning. JAMA Netw Open. 2019 Aug 2;2(8):e197939.
Wang R, Wang G, Henao R. Discriminative Clustering for Robust Unsupervised Domain Adaptation. 2019.
Dov D, Kovalsky S, Cohen J, Range D, Henao R, Carin L. Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. Proceedings of Machine Learning Research, 2019, Vol 106. 2019 Mar 29;
Wang R, Wang G, Henao R. Discriminative Clustering for Robust Unsupervised Domain Adaptation. CoRR. 2019;abs/1905.13331.
Liang KJ, Wang G, Li Y, Henao R, Carin L. Kernel-based approaches for sequence modeling: Connections to neural methods. Advances in Neural Information Processing Systems. 2019 Jan 1;32.
Cheng P, Liu C, Li C, Shen D, Henao R, Carin L. Straight-Through Estimator as Projected Wasserstein Gradient Flow. CoRR. 2019;abs/1910.02176.
Lydon EC, Bullard C, Aydin M, Better OM, Mazur A, Nicholson BP, et al. A host gene expression approach for identifying triggers of asthma exacerbations. PLoS One. 2019;14(4):e0214871.
Han S, Tian J, Kelly M, Selvakumaran V, Henao R, Rubin GD, et al. Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2019.
Limkakeng AT, Henao R, Voora D, O’Connell T, Griffin M, Tsalik EL, et al. Pilot study of myocardial ischemia-induced metabolomic changes in emergency department patients undergoing stress testing. PLoS One. 2019;14(2):e0211762.
Liang KJ, Wang G, Li Y, Henao R, Carin L. Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. In: Wallach HM, Larochelle H, Beygelzimer A, d’Alché-Buc F, Fox EB, Garnett R, editors. NeurIPS. 2019. p. 3387–98.
Dov D, Kovalsky SZ, Cohen J, Range DE, Henao R, Carin L. Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. Proceedings of Machine Learning Research. 2019 Jan 1;106:553–70.
Liu Y, Fu W, Selvakumaran V, Phelan M, Segars WP, Samei E, et al. Deep learning of 3D computed tomography (CT) images for organ segmentation using 2D multi-channel SegNet model. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2019.
Wang W, Tao C, Gan Z, Wang G, Chen L, Zhang X, et al. Improving Textual Network Learning with Variational Homophilic Embeddings. In: Wallach HM, Larochelle H, Beygelzimer A, d’Alché-Buc F, Fox EB, Garnett R, editors. NeurIPS. 2019. p. 2074–85.
Chapfuwa P, Tao C, Carin L, Henao R. Survival Function Matching for Calibrated Time-to-Event Predictions. CoRR. 2019;abs/1905.08838.
Li C, Chen C, Pu Y, Henao R, Carin L. Communication-Efficient stochastic gradient mcmc for neural networks. In: 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. 2019. p. 4173–80.
Wang W, Tao C, Gan Z, Wang G, Chen L, Zhang X, et al. Improving textual network learning with variational homophilic embeddings. Advances in Neural Information Processing Systems. 2019 Jan 1;32.
Benitez M, Tian J, Kelly M, Selvakumaran V, Phelan M, Mazurowski M, et al. Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2019.
Glass O, Henao R, Patel K, Guy CD, Gruss HJ, Syn W-K, et al. Serum Interleukin-8, Osteopontin, and Monocyte Chemoattractant Protein 1 Are Associated With Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Hepatol Commun. 2018 Nov;2(11):1344–55.
Fourati S, Talla A, Mahmoudian M, Burkhart JG, Klén R, Henao R, et al. A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nat Commun. 2018 Oct 24;9(1):4418.
Bradley T, Peppa D, Pedroza-Pacheco I, Li D, Cain DW, Henao R, et al. RAB11FIP5 Expression and Altered Natural Killer Cell Function Are Associated with Induction of HIV Broadly Neutralizing Antibody Responses. Cell. 2018 Oct 4;175(2):387-399.e17.
Sweeney TE, Azad TD, Donato M, Haynes WA, Perumal TM, Henao R, et al. Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med. 2018 Jun;46(6):915–25.
Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, et al. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun. 2018 Feb 15;9(1):694.
Chapfuwa P, Tao C, Li C, Page C, Goldstein BA, Carin L, et al. Adversarial Time-to-Event Modeling. In: Dy JG, Krause A, editors. ICML. PMLR; 2018. p. 734–43.
Shen D, Zhang Y, Henao R, Su Q, Carin L. Deconvolutional latent-variable model for text sequence matching. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. 2018 Jan 1;5438–45.
Tao C, Chen L, Henao R, Feng J, Carin L. X² generative adversarial network. In: 35th International Conference on Machine Learning, ICML 2018. 2018. p. 7787–96.
Tao C, Chen L, Henao R, Feng J, Carin L. Chi-square Generative Adversarial Network. In: Dy JG, Krause A, editors. ICML. PMLR; 2018. p. 4894–903.
Wang G, Li C, Wang W, Zhang Y, Shen D, Zhang X, et al. Joint Embedding of Words and Labels for Text Classification. In: Gurevych I, Miyao Y, editors. ACL (1). Association for Computational Linguistics; 2018. p. 2321–31.
Tao C, Chen L, Zhang R, Henao R, Carin L. Variational Inference and Model Selection with Generalized Evidence Bounds. In: INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 80. 2018.
Shen D, Zhang X, Henao R, Carin L. Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. In: Riloff E, Chiang D, Hockenmaier J, Tsujii J, editors. EMNLP. Association for Computational Linguistics; 2018. p. 1829–38.
Pu Y, Dai S, Gan Z, Wang W, Wang G, Zhang Y, et al. JointGAN: Multi-domain joint distribution learning with generative adversarial nets. 35th International Conference on Machine Learning, ICML 2018. 2018 Jan 1;9:6626–35.
Tao C, Chen L, Henao R, Feng J, Carin L. Supplementary material for "x² Generative Adversarial Net". In: 35th International Conference on Machine Learning, ICML 2018. 2018. p. 7797–809.
Shen D, Zhang X, Henao R, Carin L. Improved semantic-aware network embedding with fine-grained word alignment. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. 2018 Jan 1;1829–38.
Shen D, Zhang Y, Henao R, Su Q, Carin L. Deconvolutional Latent-Variable Model for Text Sequence Matching. In: McIlraith SA, Weinberger KQ, editors. AAAI. AAAI Press; 2018. p. 5438–45.
Shen D, Wang G, Wang W, Min MR, Su Q, Zhang Y, et al. Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. In: Gurevych I, Miyao Y, editors. ACL (1). Association for Computational Linguistics; 2018. p. 440–50.
Pu Y, Dai S, Gan Z, Wang W, Wang G, Zhang Y, et al. JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. In: Dy JG, Krause A, editors. ICML. PMLR; 2018. p. 4148–57.
Tao C, Chen L, Zhang R, Henao R, Carin L. Variational inference and model selection with generalized evidence bounds. In: 35th International Conference on Machine Learning, ICML 2018. 2018. p. 1419–35.
Poore GD, Ko ER, Valente A, Henao R, Sumner K, Hong C, et al. A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies. Front Microbiol. 2018;9:2957.
Shen D, Su Q, Chapfuwa P, Wang W, Wang G, Henao R, et al. NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. In: Gurevych I, Miyao Y, editors. ACL (1). Association for Computational Linguistics; 2018. p. 2041–50.
Zhang X, Henao R, Gan Z, Li Y, Carin L. Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. Proceedings of Machine Learning Research. 2018 Jan 1;85:280–94.
Shen D, Su Q, Chapfuwa P, Wang W, Wang G, Carin L, et al. NasH: Toward end-to-end neural architecture for generative semantic hashing. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). 2018 Jan 1;1:2041–50.
Chapfuwa P, Tao C, Li C, Page C, Goldstein B, Carin L, et al. Adversarial time-to-event modeling. 35th International Conference on Machine Learning, ICML 2018. 2018 Jan 1;2:1143–56.
Shen D, Wang G, Wang W, Min MR, Su Q, Zhang Y, et al. Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). 2018 Jan 1;1:440–50.
Wang G, Li C, Wang W, Zhang Y, Shen D, Zhang X, et al. Joint embedding of words and labels for text classification. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). 2018 Jan 1;1:2321–31.
Zhang X, Henao R, Gan Z, Li Y, Carin L. Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. In: Doshi-Velez F, Fackler J, Jung K, Kale DC, Ranganath R, Wallace BC, et al., editors. MLHC. PMLR; 2018. p. 280–94.
Wegermann K, Henao R, Diehl AM, Murphy SK, Abdelmalek MF, Moylan CA. Branched chain amino acid transaminase 1 (BCAT1) is overexpressed and hypomethylated in patients with non-alcoholic fatty liver disease who experience adverse clinical events: A pilot study. PLoS One. 2018;13(9):e0204308.
Rusincovitch SA, Wruck L, Henao R, Rodgers L, Dunning A, Merrill P, et al. The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. In: AMIA. AMIA; 2018.
Hald DH, Henao R, Winther O. Gaussian process based independent analysis for temporal source separation in fMRI. Neuroimage. 2017 May 15;152:563–74.
Patel YA, Henao R, Moylan CA, Guy CD, Piercy DL, Diehl AM, et al. Reply to Kim et al. Am J Gastroenterol. 2017 May;112(5):807–8.
Burke TW, Henao R, Soderblom E, Tsalik EL, Thompson JW, McClain MT, et al. Nasopharyngeal Protein Biomarkers of Acute Respiratory Virus Infection. EBioMedicine. 2017 Mar;17:172–81.
Pu Y, Gan Z, Henao R, Li C, Han S, Carin L. VAE Learning via Stein Variational Gradient Descent. In: Guyon I, Luxburg UV, Bengio S, Wallach H, Fergus R, Vishwanathan S, et al., editors. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017). NEURAL INFORMATION PROCESSING SYSTEMS (NIPS); 2017.
Rusincovitch SA, Henao R, Gao M, Carin L, Rogers U, Neely NB, et al. Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population. In: AMIA. AMIA; 2017.
Zhang Y, Gan Z, Fan K, Chen Z, Henao R, Shen D, et al. Adversarial feature matching for text generation. 34th International Conference on Machine Learning, ICML 2017. 2017 Jan 1;8:6093–102.
Pu Y, Gan Z, Henao R, Li C, Han S, Carin L. Stein Variational Autoencoder. CoRR. 2017;abs/1704.05155.
Pu Y, Wang W, Henao R, Chen L, Gan Z, Li C, et al. Adversarial Symmetric Variational Autoencoder. In: Guyon I, Luxburg UV, Bengio S, Wallach H, Fergus R, Vishwanathan S, et al., editors. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017). NEURAL INFORMATION PROCESSING SYSTEMS (NIPS); 2017.
Zhang Y, Chen C, Gan Z, Henao R, Carin L. Stochastic gradient monomial gamma sampler. 34th International Conference on Machine Learning, ICML 2017. 2017 Jan 1;8:6083–92.
Pu Y, Gan Z, Henao R, Li C, Han S, Carin L. VAE learning via Stein variational gradient descent. In: Advances in Neural Information Processing Systems. 2017. p. 4237–46.
Zhang Y, Shen D, Wang G, Gan Z, Henao R, Carin L. Deconvolutional Paragraph Representation Learning. In: Guyon I, Luxburg UV, Bengio S, Wallach HM, Fergus R, Vishwanathan SVN, et al., editors. NIPS. 2017. p. 4169–79.
Zhang Y, Shen D, Wang G, Gan Z, Henao R, Carin L. Deconvolutional paragraph representation learning. Advances in Neural Information Processing Systems. 2017 Jan 1;2017-December:4170–80.
Li C, Liu H, Chen C, Pu Y, Chen L, Henao R, et al. Towards Understanding Adversarial Learning for Joint Distribution Matching. CoRR. 2017;abs/1709.01215.
Zhang Y, Gan Z, Fan K, Chen Z, Henao R, Shen D, et al. Adversarial Feature Matching for Text Generation. In: Precup D, Teh YW, editors. ICML. PMLR; 2017. p. 4006–15.
Li C, Liu H, Chen C, Pu Y, Chen L, Henao R, et al. ALICE: Towards understanding adversarial learning for joint distribution matching. In: Advances in Neural Information Processing Systems. 2017. p. 5496–504.
Li C, Liu H, Chen C, Pu Y, Chen L, Henao R, et al. ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. In: Guyon I, Luxburg UV, Bengio S, Wallach H, Fergus R, Vishwanathan S, et al., editors. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017). NEURAL INFORMATION PROCESSING SYSTEMS (NIPS); 2017.
Zhang Y, Chen C, Gan Z, Henao R, Carin L. Stochastic Gradient Monomial Gamma Sampler. In: INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 70. 2017.
Pu Y, Wang W, Henao R, Chen L, Gan Z, Li C, et al. Adversarial symmetric variational autoencoder. Advances in Neural Information Processing Systems. 2017 Jan 1;2017-December:4331–40.
Gan Z, Pu Y, Henao R, Li C, He X, Carin L. Learning generic sentence representations using convolutional neural networks. In: EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings. 2017. p. 2390–400.
Komives E, Rusincovitch SA, Paat J, Carin L, Costello D, Gao M, et al. Guiding Principles for the Duke Connected Care Predictive Modeling Pilot. In: AMIA. AMIA; 2017.
Patel YA, Henao R, Moylan CA, Guy CD, Piercy DL, Diehl AM, et al. Vitamin D is Not Associated With Severity in NAFLD: Results of a Paired Clinical and Gene Expression Profile Analysis. Am J Gastroenterol. 2016 Nov;111(11):1591–8.
Patel YA, Henao R, Moylan CA, Guy CD, Piercy DL, Diehl AM, et al. Vitamin D is Not Associated with Histologic Severity in NAFLD: Results of a Paired Clinical and Hepatic Gene Expression Profile Analysis. In: HEPATOLOGY. WILEY; 2016. p. 577A-577A.
Wegermann K, Henao R, Pan Y, Diehl AM, Abdelmalek MF, Moylan CA. BCAT1 is Associated with Clinical Decompensation in NAFLD: A Pilot Study. In: HEPATOLOGY. WILEY; 2016. p. 577A-577A.
Zhang Y, Zhao Y, David L, Henao R, Carin L. Dynamic poisson factor analysis. In: Proceedings - IEEE International Conference on Data Mining, ICDM. 2016. p. 1359–64.
Fan K, Zhang Y, Henao R, Heller K. Triply stochastic variational inference for non-linear beta process factor analysis. In: Proceedings - IEEE International Conference on Data Mining, ICDM. 2016. p. 121–30.
Henao R, Lu JT, Lucas JE, Ferranti J, Carin L. Electronic health record analysis via deep poisson factor models. Journal of Machine Learning Research. 2016 Apr 1;17.
McClain MT, Henao R, Williams J, Nicholson B, Veldman T, Hudson L, et al. Differential evolution of peripheral cytokine levels in symptomatic and asymptomatic responses to experimental influenza virus challenge. Clin Exp Immunol. 2016 Mar;183(3):441–51.
Tsalik EL, Henao R, Nichols M, Burke T, Ko ER, McClain MT, et al. Host gene expression classifiers diagnose acute respiratory illness etiology. Sci Transl Med. 2016 Jan 20;8(322):322ra11.
Gan Z, Yuan X, Henao R, Tsalik EL, Carin L. Inference of gene networks associated with the host response to infectious disease. In: Big Data over Networks. Cambridge University Press; 2016. p. 365–90.
Pu Y, Gan Z, Henao R, Yuan X, Li C, Stevens A, et al. Variational Autoencoder for Deep Learning of Images, Labels and Captions. In: Lee DD, Sugiyama M, Luxburg UV, Guyon I, Garnett R, editors. NIPS. 2016. p. 2352–60.
Yizhe Z, Henao R, Li C, Carin L. Bayesian dictionary learning with Gaussian processes and sigmoid belief networks. In: IJCAI International Joint Conference on Artificial Intelligence. 2016. p. 2364–70.
Gan Z, Pu Y, Henao R, Li C, He X, Carin L. Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. CoRR. 2016;abs/1611.07897.
Zhang Y, Henao R, Carin L, Zhong J, Hartemink AJ. Learning a Hybrid Architecture for Sequence Regression and Annotation. In: Schuurmans D, Wellman MP, editors. AAAI. AAAI Press; 2016. p. 1415–21.
Zhang Y, Chen C, Henao R, Carin L. Laplacian Hamiltonian Monte Carlo. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. p. 98–114.
Zhang Y, Wang X, Chen C, Henao R, Fan K, Carin L. Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. In: Lee DD, Sugiyama M, Luxburg UV, Guyon I, Garnett R, editors. NIPS. 2016. p. 1741–9.
Zhang Y, Wang X, Chen C, Henao R, Fan K, Carin L. Towards unifying hamiltonian Monte Carlo and Slice sampling. In: Advances in Neural Information Processing Systems. 2016. p. 1749–57.
Song Z, Henao R, Carlson D, Carin L. Learning sigmoid belief networks via Monte Carlo expectation maximization. In: Artificial Intelligence and Statistics. 2016. p. 1347–55.
Pu Y, Gan Z, Henao R, Yuan X, Li C, Stevens A, et al. Variational autoencoder for deep learning of images, labels and captions. In: Advances in Neural Information Processing Systems. 2016. p. 2360–8.
Henao R, Hasanaliyeva N, Bell LN, Wulff J, Perichon R, Moylan CA, et al. Plasma Metabolomic Profiles Predict Advanced Hepatic Fibrosis in Patients with Nonalcoholic Fatty Liver Disease. In: HEPATOLOGY. WILEY-BLACKWELL; 2015. p. 290A-291A.
Vikeså J, Møller AKH, Kaczkowski B, Borup R, Winther O, Henao R, et al. Cancers of unknown primary origin (CUP) are characterized by chromosomal instability (CIN) compared to metastasis of know origin. BMC Cancer. 2015 Mar 19;15:151.
Yuan X, Henao R, Tsalik EL, Langley RJ, Carin L. Non-Gaussian discriminative factor models via the max-margin rank-likelihood. 32nd International Conference on Machine Learning, ICML 2015. 2015 Jan 1;2:1254–63.
Gan Z, Henao R, Carlson D, Carin L. Learning deep sigmoid belief networks with data augmentation. In: Artificial Intelligence and Statistics. 2015. p. 268–76.
Gan Z, Li C, Henao R, Carlson DE, Carin L. Deep Temporal Sigmoid Belief Networks for Sequence Modeling. In: Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R, editors. NIPS. 2015. p. 2467–75.
Raiy P, Hu C, Henao R, Carin L. Large-scale Bayesian multi-label learning via topic-based label embeddings. In: Advances in Neural Information Processing Systems. 2015. p. 3222–30.
Gan Z, Chen C, Henao R, Carlson D, Carin L. Scalable Deep Poisson Factor Analysis for Topic Modeling. In: ICML. 2015.
Lian W, Henao R, Rao V, Lucas J, Carin L. A multitask point process predictive model. In: 32nd International Conference on Machine Learning, ICML 2015. 2015. p. 2030–8.
Gan Z, Li C, Henao R, Carlson DE, Carin L. Deep temporal sigmoid belief networks for sequence modeling. Advances in Neural Information Processing Systems. 2015;2467–75.
Henao R, Gan Z, Lu J, Carin L. Deep poisson factor modeling. In: Advances in Neural Information Processing Systems. 2015. p. 2800–8.
Tsalik EL, Langley RJ, Dinwiddie DL, Miller NA, Yoo B, van Velkinburgh JC, et al. An integrated transcriptome and expressed variant analysis of sepsis survival and death. Genome Med. 2014;6(11):111.
Henao R, Yuan X, Carin L. Bayesian nonlinear support vector machines and discriminative factor modeling. In: Advances in Neural Information Processing Systems. 2014. p. 1754–62.
Benjamin AM, Thompson JW, Soderblom EJ, Geromanos SJ, Henao R, Kraus VB, et al. A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information. BMC Bioinformatics. 2013 Dec 16;14:364.
Ouinones QJ, Ma Q, Henao R, Lucas J, Riess ML, Bain J, et al. Proteomnic and Metabolomic Profiling After Isehemia-Reperfusion Injury Reveals Bottlenecks That Underlie Cardioprotection in Hibernating Mammals. In: CIRCULATION. LIPPINCOTT WILLIAMS & WILKINS; 2013.
Henao R, Thompson JW, Moseley MA, Ginsburg GS, Carin L, Lucas JE. Latent protein trees. Annals of Applied Statistics. 2013 Jun 1;7(2):691–713.
Kurokawa M, Kim J, Geradts J, Matsuura K, Liu L, Ran X, et al. A network of substrates of the E3 ubiquitin ligases MDM2 and HUWE1 control apoptosis independently of p53. Sci Signal. 2013 May 7;6(274):ra32.
Henao R, Murray J, Ginsburg G, Carin L, Lucas JE. Patient clustering with uncoded text in electronic medical records. AMIA Annu Symp Proc. 2013;2013:592–9.
Henao R, Thompson JW, Moseley MA, Ginsburg GS, Carin L, Lucas JE. Hierarchical factor modeling of proteomics data. 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012. 2012 May 8;
Henao R, Lucas JE. Efficient hierarchical clustering for continuous data. 2012 Apr 20;
Henao R, Winther O. Predictive active set selection methods for Gaussian processes. Neurocomputing. 2012 Mar 15;80:10–8.
Rossing M, Borup R, Henao R, Winther O, Vikesaa J, Niazi O, et al. Down-regulation of microRNAs controlling tumourigenic factors in follicular thyroid carcinoma. J Mol Endocrinol. 2012 Feb;48(1):11–23.
Carin L, Hero A, Lucas J, Dunson D, Chen M, Heñao R, et al. High-Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections. IEEE Signal Process Mag. 2012 Jan 1;29(1):108–23.
Friis M, Martin-Bertelsen T, Friis-Hansen L, Winther O, Henao R, Sørensen MS, et al. Gene expression of the endolymphatic sac. Acta Otolaryngol. 2011 Dec;131(12):1257–63.
Henao R, Winther O. Sparse linear identifiable multivariate modeling. Journal of Machine Learning Research. 2011 Mar 1;12:863–905.
Henao R, Winther O. PASS-GP: Predictive active set selection for Gaussian processes. Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2010. 2010 Nov 24;148–53.
Borup R, Rossing M, Henao R, Yamamoto Y, Krogdahl A, Godballe C, et al. Molecular signatures of thyroid follicular neoplasia. Endocr Relat Cancer. 2010 Sep;17(3):691–708.
Walder C, Henao R, Mørup M, Hansen LK. Semi-Supervised Kernel PCA. CoRR. 2010;abs/1008.1398.
Henao R, Winther O. Bayesian sparse factor models and DAGs inference and comparison. In: Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 2009. p. 736–44.
Alvarez López MA, Henao R, Orozco A. Myocardial ischemia detection using Hidden Markov principal component analysis. IFMBE Proceedings. 2008 Jan 1;18:99–103.
Alvarez M, Henao R, Castellanos G, Godino JI, Orozco A. Kernel Principal Component analysis through time for voice disorder classification. Conference proceedings : . Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Conference. 2006;5511–4.
Alvarez M, Henao R. Probabilistic kernel principal component analysis through time. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2006. p. 747–54.
Alvarez M, Henao R, Castellanos G, Godino JI, Orozco A. Kernel principal component analysis through time for voice disorder classification. In: 2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15. IEEE; 2006. p. 2620-+.
Alvarez M, Henao R, Castellanos G, Godino JI, Orozco A. Kernel Principal Component analysis through time for voice disorder classification. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:5511–4.
Rengifo CL, Alvarez DA, Henao R, Castellanos G, Hurtado JE. Active Learning on the Classification of Voice Pathologies. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. 2004.

In The News

Duke Researchers Look to Help Protect Astronaut's Eyes in Space (Sep 14, 2020 | Precision Medicine)
New Collaborative Seed Grant Program Gives Eight Awards (Mar 16, 2016 | )