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2020 – today
- 2024
[i13]Mert Ketenci, Iñigo Urteaga, Victor Alfonso Rodriguez, Noémie Elhadad, Adler J. Perotte:
Variational Shapley Network: A Probabilistic Approach to Self-Explaining Shapley values with Uncertainty Quantification. CoRR abs/2402.04211 (2024)- 2023
- [j17]Tian Kang, Yingcheng Sun
, Jae Hyun Kim, Casey N. Ta, Adler J. Perotte, Kayla Schiffer, Mutong Wu, Yang Zhao, Nour Moustafa-Fahmy, Yifan Peng, Chunhua Weng:
EvidenceMap: a three-level knowledge representation for medical evidence computation and comprehension. J. Am. Medical Informatics Assoc. 30(6): 1022-1031 (2023) - [c29]Mert Ketenci, Shreyas Bhave, Noemie Elhadad, Adler J. Perotte:
Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling. MLHC 2023: 360-380 - [i12]Mert Ketenci, Adler J. Perotte, Noémie Elhadad, Iñigo Urteaga:
A Coreset-based, Tempered Variational Posterior for Accurate and Scalable Stochastic Gaussian Process Inference. CoRR abs/2311.01409 (2023) - [i11]Mert Ketenci, Shreyas Bhave, Noémie Elhadad, Adler J. Perotte:
Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling. CoRR abs/2311.01660 (2023) - 2022
- [i10]David Ouyang, John Theurer, Nathan R. Stein, J. Weston Hughes, Pierre A. Elias, Bryan He, Neal Yuan, Grant Duffy, Roopinder K. Sandhu, Joseph Ebinger, Patrick Botting, Melvin Jujjavarapu, Brian Claggett, James E. Tooley, Tim Poterucha, Jonathan H. Chen, Michael Nurok, Marco V. Perez, Adler J. Perotte, James Y. Zou, Nancy R. Cook, Sumeet S. Chugh, Susan Cheng, Christine M. Albert:
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality. CoRR abs/2205.03242 (2022) - 2021
- [j16]Tian Kang, Adler J. Perotte, Youlan Tang, Casey N. Ta, Chunhua Weng:
UMLS-based data augmentation for natural language processing of clinical research literature. J. Am. Medical Informatics Assoc. 28(4): 812-823 (2021) - [j15]Victor Alfonso Rodriguez, Shreyas Bhave, Ruijun Chen, Chao Pang, George Hripcsak, Soumitra Sengupta, Noemie Elhadad, Robert A. Green, Jason S. Adelman, Katherine Schlosser Metitiri, Pierre A. Elias, Holden Groves, Sumit Mohan, Karthik Natarajan, Adler J. Perotte:
Development and validation of prediction models for mechanical ventilation, renal replacement therapy, and readmission in COVID-19 patients. J. Am. Medical Informatics Assoc. 28(7): 1480-1488 (2021) - [j14]Tian Kang, Ali Turfah, Jaehyun Kim, Adler J. Perotte, Chunhua Weng:
A neuro-symbolic method for understanding free-text medical evidence. J. Am. Medical Informatics Assoc. 28(8): 1703-1711 (2021) - [j13]Li-heng Fu, Chris Knaplund, Kenrick Cato, Adler J. Perotte, Min-Jeoung Kang, Patricia C. Dykes, David J. Albers, Sarah Collins Rossetti:
Utilizing timestamps of longitudinal electronic health record data to classify clinical deterioration events. J. Am. Medical Informatics Assoc. 28(9): 1955-1963 (2021) - [j12]Oliver J. Bear Don't Walk IV, Tony Y. Sun, Adler J. Perotte, Noémie Elhadad:
Clinically relevant pretraining is all you need. J. Am. Medical Informatics Assoc. 28(9): 1970-1976 (2021) - [j11]Amelia J. Averitt, Patrick B. Ryan, Chunhua Weng, Adler J. Perotte:
A conceptual framework for external validity. J. Biomed. Informatics 121: 103870 (2021) - [c28]Shreyas Bhave, Pierre A. Elias, Victor Alfonso Rodriguez, Timothy Poterucha, Simi Mutasa, Jay Leb, Nir Uriel, Adler J. Perotte:
LVHNet: Detecting Cardiac Structural Abnormalities with Chest X-Rays. AMIA 2021 - [c27]Shreyas Bhave, Adler J. Perotte:
Multi-Channel LSTM for Modeling Irregularly Sampled Time Series. AMIA 2021 - [c26]Chao Pang, Xinzhuo Jiang, Krishna S. Kalluri, Matthew E. Spotnitz, Ruijun Chen, Adler J. Perotte, Karthik Natarajan:
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks. ML4H@NeurIPS 2021: 239-260 - [c25]Shreyas Bhave, Adler J. Perotte:
Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR Data. MLHC 2021: 770-789 - [c24]Xintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath:
Inverse-Weighted Survival Games. NeurIPS 2021: 2160-2172 - [i9]Mark Goldstein, Xintian Han, Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath:
X-CAL: Explicit Calibration for Survival Analysis. CoRR abs/2101.05346 (2021) - [i8]Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath:
Causal Estimation with Functional Confounders. CoRR abs/2102.08533 (2021) - [i7]Xintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath:
Inverse-Weighted Survival Games. CoRR abs/2111.08175 (2021) - [i6]Chao Pang, Xinzhuo Jiang, Krishna S. Kalluri, Matthew E. Spotnitz, Ruijun Chen, Adler J. Perotte, Karthik Natarajan:
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks. CoRR abs/2111.08585 (2021) - 2020
- [j10]Amelia J. Averitt, Natnicha Vanitchanant, Rajesh Ranganath, Adler J. Perotte:
The Counterfactual χ-GAN: Finding comparable cohorts in observational health data. J. Biomed. Informatics 109: 103515 (2020) - [j9]Amelia J. Averitt, Chunhua Weng, Patrick B. Ryan, Adler J. Perotte:
Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations. npj Digit. Medicine 3 (2020) - [c23]Amelia J. Averitt, Natnicha Vanitchanant, Rajesh Ranganath, Adler J. Perotte:
Adversarially-Learned Balancing Weights for Causal Inference. AMIA 2020 - [c22]Shreyas Bhave, Xintian Han, Rajesh Ranganath, Adler J. Perotte:
Deep Survival Analysis: The Impact of Feature Missingness. AMIA 2020 - [c21]Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler J. Perotte, Noémie Elhadad:
Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells. ML4H@NeurIPS 2020: 12-40 - [c20]Mark Goldstein, Xintian Han, Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath:
X-CAL: Explicit Calibration for Survival Analysis. NeurIPS 2020 - [c19]Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath:
Causal Estimation with Functional Confounders. NeurIPS 2020 - [i5]Amelia J. Averitt, Natnicha Vanitchanant, Rajesh Ranganath, Adler J. Perotte:
The Counterfactual χ-GAN. CoRR abs/2001.03115 (2020) - [i4]Griffin Adams, Mert Ketenci, Adler J. Perotte, Noemie Elhadad:
Zero-Shot Clinical Acronym Expansion with a Hierarchical Metadata-Based Latent Variable Model. CoRR abs/2010.02010 (2020)
2010 – 2019
- 2019
- [j8]Fernanda C. Polubriaginof, Patrick B. Ryan, Hojjat Salmasian, Andrea W. Shapiro, Adler J. Perotte, Monika M. Safford, George Hripcsak, Shaun Smith, Nicholas P. Tatonetti, David K. Vawdrey:
Challenges with quality of race and ethnicity data in observational databases. J. Am. Medical Informatics Assoc. 26(8-9): 730-736 (2019) - [c18]Amelia J. Averitt, Benjamin H. Slovis, Abdul A. Tariq, David K. Vawdrey, Adler J. Perotte:
Characterizing the Urban Opioid Epidemic Using EHR Data. AMIA 2019 - [c17]Victor Alfonso Rodriguez, Adler J. Perotte:
Learning Disease Phenotypes with Semi-Supervision. AMIA 2019 - [c16]Victor Alfonso Rodriguez, Adler J. Perotte:
Phenotype Inference with Semi-Supervised Mixed Membership Models. MLHC 2019: 304-324 - 2018
- [c15]Amelia J. Averitt, Adler J. Perotte:
Noisy-Or Risk Allocation Model for Causal Inference. AMIA 2018 - [c14]Joongheum Park, Hao Shi, Adler J. Perotte:
Development of a Machine Learning Model for Prediction of Successful Extubation and User-Friendly Implementation for Real-World Use. AMIA 2018 - [c13]Xenia Miscouridou, Adler J. Perotte, Noemie Elhadad, Rajesh Ranganath:
Deep Survival Analysis: Nonparametrics and Missingness. MLHC 2018: 244-256 - [i3]Rajesh Ranganath, Adler J. Perotte:
Multiple Causal Inference with Latent Confounding. CoRR abs/1805.08273 (2018) - [i2]Victor Alfonso Rodriguez, Adler J. Perotte:
Phenotype inference with Semi-Supervised Mixed Membership Models. CoRR abs/1812.03222 (2018) - 2017
- [c12]Amelia J. Averitt, Chunhua Weng, Adler J. Perotte:
Clinical Trial Eligibility Criteria Fail to Meet Burden of Generalizability. AMIA 2017 - [c11]Joongheum Park, Liana Tascau, Adler J. Perotte:
Lessons Learned from the Conversion of MIMIC3 to the OHDSI Common Data Model. AMIA 2017 - 2016
- [c10]David J. Albers, Adler J. Perotte, George Hripcsak:
Approaches for using temporal and other filters for next generation phenotype discovery. AMIA 2016 - [c9]Amelia J. Averitt, Adler J. Perotte:
Standardization of FDA Adverse Event Reporting System to the OHDSI Common Data Model. AMIA 2016 - [c8]Adler J. Perotte, Noemie Elhadad:
A probabilistic model for learning relationships between diagnosis codes and clinical free text. AMIA 2016 - [c7]Fernanda Polubriaginof, Hojjat Salmasian, Andrea W. Shapiro, Jennifer E. Prey, George Hripcsak, Adler J. Perotte, Nicholas P. Tatonetti, David K. Vawdrey:
Patient-provided Data Improves Race and Ethnicity Data Quality in Electronic Health Records. AMIA 2016 - [c6]Fernanda Polubriaginof, Mary Regina Boland, Adler J. Perotte, David K. Vawdrey:
Quality of Race and Ethnicity Data in Electronic Health Records. CRI 2016 - [c5]Rajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei:
Deep Survival Analysis. MLHC 2016: 101-114 - [i1]Rajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei:
Deep Survival Analysis. CoRR abs/1608.02158 (2016) - 2015
- [j7]George Hripcsak, David J. Albers, Adler J. Perotte:
Parameterizing time in electronic health record studies. J. Am. Medical Informatics Assoc. 22(4): 794-804 (2015) - [j6]Adler J. Perotte, Rajesh Ranganath, Jamie S. Hirsch, David M. Blei, Noémie Elhadad:
Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis. J. Am. Medical Informatics Assoc. 22(4): 872-880 (2015) - [j5]Rimma Pivovarov, Adler J. Perotte, Edouard Grave, John Angiolillo, Chris H. Wiggins, Noémie Elhadad:
Learning probabilistic phenotypes from heterogeneous EHR data. J. Biomed. Informatics 58: 156-165 (2015) - [c4]Mark D. Danese, Erica A. Voss, Jennifer Duryea, Michelle Gleeson, Ryan Duryea, Amy Matcho, Donald O'Hara, William E. Stephens, Adler J. Perotte, Lee Evans, Christian G. Reich:
Feasibility of Converting the Medicare Synthetic Public Use Data Into a Standardized Data Model for Clinical Research Informatics. AMIA 2015 - [c3]Rajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei:
The Survival Filter: Joint Survival Analysis with a Latent Time Series. UAI 2015: 742-751 - 2014
- [j4]Adler J. Perotte, Rimma Pivovarov, Karthik Natarajan, Nicole Gray Weiskopf, Frank D. Wood, Noemie Elhadad:
Diagnosis code assignment: models and evaluation metrics. J. Am. Medical Informatics Assoc. 21(2): 231-237 (2014) - [r1]Frank D. Wood, Adler J. Perotte:
Mixed Membership Classification for Documents with Hierarchically Structured Labels. Handbook of Mixed Membership Models and Their Applications 2014: 305-323 - 2013
- [j3]Adler J. Perotte, George Hripcsak:
Temporal Properties of Diagnosis Code Time Series in Aggregate. IEEE J. Biomed. Health Informatics 17(2): 477-483 (2013) - 2011
- [j2]George Hripcsak, David J. Albers, Adler J. Perotte:
Exploiting time in electronic health record correlations. J. Am. Medical Informatics Assoc. 18(Supplement): 109-115 (2011) - [c2]Adler J. Perotte, Frank D. Wood, Noemie Elhadad, Nicholas Bartlett:
Hierarchically Supervised Latent Dirichlet Allocation. NIPS 2011: 2609-2617
2000 – 2009
- 2009
- [c1]Richard Socher, Samuel Gershman, Adler J. Perotte, Per B. Sederberg, David M. Blei, Kenneth A. Norman:
A Bayesian Analysis of Dynamics in Free Recall. NIPS 2009: 1714-1722 - 2005
- [j1]Kenneth A. Norman, Ehren L. Newman, Adler J. Perotte:
Methods for reducing interference in the Complementary Learning Systems model: Oscillating inhibition and autonomous memory rehearsal. Neural Networks 18(9): 1212-1228 (2005)
Coauthor Index
aka: Noemie Elhadad
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