Transforming electronic health records

MedKnowts is a smarter electronic health record (EHR) that employs machine learning to speed up clinicians’ workflows, since clinicians often spend more time interfacing with the EHR than with patients. Medknowts can:

  • Autocomplete and automatically structure medical terms
  • Proactively surface relevant information (e.g. historical lab tests, pertinent notes)
  • Help autopopulate sections of the note
  • Create cleaner notes that can be translated into patient-friendlier language

Fill out this form to keep up-to-date with our project!

Demo

Additional Videos

Press

Publications on MedKnowts

.js-id-MedKnowts

Towards Verifiable Text Generation with Symbolic References

Lucas Torroba Hennigen, Shannon Shen, Aniruddha Nrusimha, Bernhard Gapp, David Sontag, Yoon Kim
2024 COLM 2024
PDF Code

Learning to Decode Collaboratively with Multiple Language Models

Shannon Shen, Hunter Lang, Bailin Wang, Yoon Kim, David Sontag
2024 ACL 2024
PDF Code

Prediction-powered Generalization of Causal Inferences

Ilker Demirel, Ahmed Alaa, Anthony Philippakis, David Sontag
2024 ICML 2024
PDF Code

A Data-Centric Approach to Generate Faithful and High Quality Patient Summaries with Large Language Models

Stefan Hegselmann, Shannon Shen, Florian Gierse, Monica Agrawal, David Sontag, Xiaoyi Jiang
2024 Conference on Health, Inference, and Learning (CHIL) 2024
PDF

Benchmarking observational studies with experimental data under right-censoring

Ilker Demirel, Edward De Brouwer, Zeshan Hussain, Michael Oberst, Anthony A Philippakis, David Sontag
2024 AISTATS 2024
PDF Code

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing

Sharon Jiang, Barbara D Lam, Monica Agrawal, Shannon Shen, Nicholas Kurtzman, Steven Horng, David R Karger, David Sontag
2024 Journal of the American Medical Informatics Association (JAMIA)
PDF

Joint AI-driven event prediction and longitudinal modeling in newly diagnosed and relapsed multiple myeloma

Zeshan Hussain, Edward De Brouwer, Rebecca Boiarsky, Sama Setty, Neeraj Gupta, Guohui Liu, Cong Li, Jaydeep Srimani, Jacob Zhang, Rich Labotka, others
2024 NPJ Digital Medicine

Effective Human-AI Teams via Learned Natural Language Rules and Onboarding

Hussein Mozannar, Jimin J Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag
2023 Advances in neural information processing systems (NeurIPS)
Code

Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes

Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David Karger, David Sontag
2023 Machine Learning for Healthcare Conference (MLHC), 2023
PDF

Large-Scale Study of Temporal Shift in Health Insurance Claims

Christina X Ji, Ahmed M Alaa, David Sontag
2023 Conference on Health, Inference, and Learning
PDF Code

A Deep Dive into Single-Cell RNA Sequencing Foundation Models

Rebecca Boiarsky, Nalini M. Singh, Alejandro Buendia, Gad Getz, David Sontag
2023 bioRxiv
DOI URL

Conformalized Unconditional Quantile Regression

Ahmed Alaa, Zeshan Hussain, David Sontag
2023 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)

Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions

Zeshan Hussain, Ming-Chieh Shih, Michael Oberst, Ilker Demirel, David Sontag
2023 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

TabLLM: Few-shot Classification of Tabular Data with Large Language Models

Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag
2023 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF Code

Who Should Predict? Exact Algorithms For Learning to Defer to Humans

Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag
2023 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF Code

Training Subset Selection for Weak Supervision

Hunter Lang, Aravindan Vijayaraghavan, David Sontag
2022 Advances in Neural Information Processing Systems
PDF

Evaluating Robustness to Dataset Shift via Parametric Robustness Sets

Nikolaj Thams, Michael Oberst, David Sontag
2022 Advances in Neural Information Processing Systems (NeurIPS)
PDF Code

Falsification before Extrapolation in Causal Effect Estimation

Zeshan Hussain, Michael Oberst, Ming-Chieh Shih, David Sontag
2022 Advances in Neural Information Processing Systems (NeurIPS)
PDF

Sample Efficient Learning of Predictors that Complement Humans

Mohammad-Amin Charusaie, Hussein Mozannar, David Sontag, Samira Samadi
2022 Proceedings of the Thirty-Eighth International Conference on Machine Learning (ICML)
PDF Code

Co-training Improves Prompt-based Learning for Large Language Models

Hunter Lang, Monica Agrawal, Yoon Kim, David Sontag
2022 Proceedings of the Thirty-Eighth International Conference on Machine Learning (ICML)
PDF

Bias-robust Integration of Observational and Experimental Estimators

Michael Oberst, Alexander D'Amour, Minmin Chen, Yuyan Wang, David Sontag, Steve Yadlowsky
2022 arXiv preprint (2205.10467)
PDF

Clustering Interval-Censored Time-Series for Disease Phenotyping

Irene Chen, Rahul Krishnan, David Sontag
2022 Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI)
PDF

ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography

Ahmed Alaa, Anthony Philippakis, David Sontag
2022 Advances in Neural Information Processing Systems Datasets and Benchmarks Track
PDF

Large Language Models are Few-Shot Clinical Information Extractors

Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David Sontag
2022 Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
PDF

Leveraging Time Irreversibility with Order-Contrastive Pre-training

Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David Sontag
2022 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis

Rebecca Boiarsky, Nicholas J Haradhvala, Jean-Baptiste Alberge, Romanos Sklavenitis-Pistofidis, Tarek H Mouhieddine, Oksana Zavidij, Ming-Chieh Shih, Danielle Firer, Mendy Miller, Habib El-Khoury, Shankara K Anand, Francois Aguet, David Sontag, Irene M Ghobrial, Gad Getz
2022 Nature Communications
PDF Code

Teaching Humans When To Defer to a Classifier via Exemplars

Hussein Mozannar, Arvind Satyanarayan, David Sontag
2022 Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI)
PDF Code

The Potential For Bias In Machine Learning And Opportunities For Health Insurers To Address It

Stephanie S Gervasi, Irene Chen, Aaron Smith-McLallen, David Sontag, Ziad Obermeyer, Michael Vennera, Ravi Chawla
2022 Health Affairs
PDF

Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models

Rickard Karlsson, Martin Willbo, Zeshan Hussain, Rahul G Krishnan, David Sontag, Fredrik D Johansson
2022 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance

Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leora Horwitz, David Sontag
2021 Proceedings of the 35th Conference on Neural Information Processing Systems
PDF Code

MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records

Luke Murray, Divya Gopinath, Monica Agrawal, Steven Horng, David Sontag, David Karger
2021 UIST ‘21: The 34th Annual ACM Symposium on User Interface Software and Technology
PDF

Graph cuts always find a global optimum for Potts models (with a catch)

Hunter Lang, David Sontag, Aravindan Vijayaraghavan
2021 Proceedings of the Thirty-Eighth International Conference on Machine Learning (ICML)
PDF

Neural Pharmacodynamic State Space Modeling

Zeshan Hussain, Rahul G Krishnan, David Sontag
2021 Proceedings of the Thirty-Eighth International Conference on Machine Learning (ICML)
PDF Code

Regularizing towards Causal Invariance: Linear Models with Proxies

Michael Oberst, Nikolaj Thams, Jonas Peters, David Sontag
2021 Proceedings of the Thirty-Eighth International Conference on Machine Learning (ICML)
PDF Code

Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative

Ariel Levy, Monica Agrawal, Arvind Satyanarayan, David Sontag
2021 CHI Conference on Human Factors in Computing Systems
PDF

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer

Matthew Alkaitis, Monica Agrawal, Gregory Riely, Pedram Razavi, David Sontag
2021 JCO Clinical Cancer Informatics
PDF DOI

Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

Christina X Ji, Michael Oberst, Sanjat Kanjilal, David Sontag
2021 AMIA 2021 Virtual Informatics Summit
PDF Code

Beyond perturbation stability: LP recovery guarantees for MAP inference on noisy stable instances

Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan
2021 Proceedings of the Twenty-Fourth International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming

Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka
2021 Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Deep Contextual Clinical Prediction with Reverse Distillation

Rohan Kodialam, Rebecca Boiarsky, Justin Lim, Neil Dixit, Aditya Sai, David Sontag
2021 Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence
PDF

Directing Human Attention in Event Localization for Clinical Timeline Creation

Jason Zhao, Monica Agrawal, Pedram Razavi, David Sontag
2021 Proceedings of the Machine Learning for Healthcare Conference
PDF

MEng Thesis: Identifying Heterogeneity in Decision-Making

Justin Lim
2021
PDF

Pulse of the Pandemic: Iterative Topic Filtering for Clinical Information Extraction from Social Media

Julia Wu, Venkatesh Sivaraman, Dheekshita Kumar, Juan M. Banda, David Sontag
2021 Journal of Biomedical Informatics
PDF DOI

A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection

Sanjat Kanjilal, Michael Oberst, Sooraj Boominathan, Helen Zhou, David C. Hooper, David Sontag
2020 Science Translational Medicine
PDF Code DOI

Characterization of Overlap in Observational Studies

Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David Sontag, Kush R. Varshney
2020 Proceedings of the Twenty-Third International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF Code

Consistent Estimators for Learning to Defer to an Expert

Hussein Mozannar, David Sontag
2020 Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML)
PDF

Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models

Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag
2020 Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML)
PDF Code

Estimation of Bounds on Potential Outcomes For Decision Making

Maggie Makar, Fredrik Johansson, John Guttag, David Sontag
2020 Proceedings of the Thirty-Seventh International Conference on Machine Learning (ICML)
PDF

Fast, Structured Clinical Documentation via Contextual Autocomplete

Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag
2020 Proceedings of the Machine Learning for Healthcare Conference
PDF

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David Sontag
2020 arXiv preprint arXiv:2001.07426
PDF

MEng Thesis: Learning Treatment Policies for Empiric Antibiotic Prescription

Sooraj Boominathan
2020
PDF

MEng Thesis: ML-Driven Clinical Documentation

Divya Gopinath
2020
PDF

MEng Thesis: Pipelines for Deep Patient-Level Clinical Outcome Prediction

Rohan Kodialam
2020
PDF

PhD Thesis: Advances in deep generative modeling for clinical data

Rahul Krishnan
2020
PDF

Predicting human health from biofluid-based metabolomics using machine learning

Ethan D Evans, Claire Duvallet, Nathaniel D Chu, Michael K Oberst, Michael A Murphy, Isaac Rockafellow, David Sontag, Eric J Alm
2020 Scientific Reports
PDF DOI

Predicting Remission Among Patients With Rheumatoid Arthritis Starting Tocilizumab Monotherapy: Model Derivation and Remission Score Development

Jamie E. Collins, Fredrik D. Johansson, Sara Gale, Seoyoung Kim, Swastina Shrestha, David Sontag, Jacklyn Stratton, Huong Trinh, Chang Xu, Elena Losina, Daniel H. Solomon
2020 ACR Open Rheumatology
PDF DOI

Robust Benchmarking for Machine Learning of Clinical Entity Extraction

Monica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David Sontag
2020 Proceedings of the Machine Learning for Healthcare Conference
PDF

Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph

Irene Chen, Monica Agrawal, Steven Horng, David Sontag
2020 Proceedings of the Pacific Symposium on Biocomputing (PSB)
PDF

Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes

Sooraj Boominathan, Michael Oberst, Helen Zhou, Sanjat Kanjilal, David Sontag
2020 Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
PDF Code

Derivation and validation of a machine learning record linkage algorithm between emergency medical services and the emergency department

Colby Redfield, Abdulhakim Tlimat, Yoni Halpern, David W Schoenfeld, Edward Ullman, David Sontag, Larry Nathanson, Steven Horng
2019 Journal of the American Medical Informatics Association
PDF DOI

Block Stability for MAP Inference

Hunter Lang, David Sontag, Aravindan Vijayaraghavan
2019 Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models

Michael Oberst, David Sontag
2019 Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML)
PDF Code

Guidelines for reinforcement learning in healthcare.

O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, F Doshi-Velez, LA Celi
2019 Nature medicine
PDF

Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces

Nathaniel R. Greenbaum, Yacine Jernite, Yoni Halpern, Shelley Calder, Larry A. Nathanson, David A. Sontag, Steven Horng
2019 International Journal of Medical Informatics
PDF DOI

Master’s Thesis: Counterfactual Policy Introspection using Structural Causal Models

Michael Oberst
2019
PDF

MEng Thesis: Fine-tuning Generative Models

Arjun Khandwelwal
2019
PDF

MEng Thesis: Modeling progression of Parkinson’s disease

Christina X Ji
2019
PDF

Overcomplete Independent Component Analysis via SDP

Anastasia Podosinnikova, Amelia Perry, Alexander Wein, Francis Bach, Alexandre d'Aspremont, David Sontag
2019 Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Support and Invertibility in Domain-Invariant Representations

Fredrik D Johansson, Rajesh Ranganath, David Sontag
2019 Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (AISTATS)
PDF

Train and Test Tightness of LP Relaxations in Structured Prediction

Ofer Meshi, Ben London, Adrian Weller, David Sontag
2019 Journal of Machine Learning Research
PDF

Cell-specific prediction and application of drug-induced gene expression profiles

Rachel Hodos, Ping Zhang, Hao Chih Lee, Qiaonan Duan, Zichen Wang, Neil R. Clark, Avi Ma'ayan, Fei Wang, Brian Kidd, Jianying Hu, David Sontag, Joel Dudley
2018 Proceedings of the Pacific Symposium on Biocomputing (PSB)
PDF

Evaluating Reinforcement Learning Algorithms in Observational Health Settings

Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David Sontag, Finale Doshi-Velez
2018
PDF

Learning Topic Models - Provably and Efficiently

Sanjeev Arora, Rong Ge, Yoni Halpern, David Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu
2018 Communications of the ACM
PDF

Learning Weighted Representations for Generalization Across Designs

Fredrik D. Johansson, Nathan Kallus, Uri Shalit, David Sontag
2018 ArXiv e-prints arXiv:1802.08598
PDF

Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions

Fredrik D Johansson
2018 arXiv preprint arXiv:1811.05975
PDF

Max-margin learning with the Bayes Factor

Rahul G. Krishnan, Arjun Khandelwal, Rajesh Ranganath, David Sontag
2018 Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI)
PDF

MEng Thesis: Large-scale Prediction of Patient-Level Antibiotic Resistance: Towards Clinical Decision Support for Improved Antimicrobial Stewardship

Helen Zhou
2018
PDF

MEng Thesis: Perturbation Stability for Approximate MAP Inference

Hunter Lang
2018
PDF

Optimality of Approximate Inference Algorithms on Stable Instances

Hunter Lang, David Sontag, Aravindan Vijayaraghavan
2018 Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AI-STATS)
PDF

PhD Thesis: Filling Gaps and Dodging Traps: Leveraging untapped potential in gene expression data for drug discovery with applications to cystic fibrosis

Rachel Hodos
2018
PDF

PhD Thesis: Learning Representations of Text through Language and Discourse Modeling: From Characters to Sentences

Yacine Jernite
2018
PDF

Recurrent Neural Networks for Multivariate Time Series with Missing Values

Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, Yan Liu
2018 Nature Scientific Reports
PDF

Semi-Amortized Variational Autoencoders

Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush
2018 Proceedings of the 35th International Conference on Machine Learning (ICML)
PDF

Why Is My Classifier Discriminatory?

Irene Chen, Fredrik D. Johansson, David Sontag
2018 Proceedings of the 32nd International Conference on Neural Information Processing Systems
PDF

Causal Effect Inference with Deep Latent-Variable Models

Christos Louizos, Uri Shalit, Joris Mooij, David Sontag, Richard S. Zemel, Max Welling
2017 Proceedings of the 31st International Conference on Neural Information Processing Systems
PDF

Contextual Autocomplete: A Novel User Interface Using Machine Learning to Improve Ontology Usage and Structured Data Capture for Presenting Problems in the Emergency Department

Nathaniel R Greenbaum, Yacine Jernite, Yoni Halpern, Shelley Calder, Larry A. Nathanson, David Sontag, Steven Horng
2017 bioRxiv
PDF

Creating an Automated Trigger for Sepsis Clinical Decision Support at Emergency Department Triage using Machine Learning

Steven Horng, David Sontag, Yoni Halpern, Yacine Jernite, Nathan I. Shapiro, Larry A. Nathanson
2017 PLoS ONE
PDF

Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning

Yacine Jernite, Samuel R Bowman, David Sontag
2017 arXiv preprint arXiv:1705.00557
PDF

Early Identification of Patients with Acute Decompensated Heart Failure

Saul Blecker, David Sontag, Leora Horwitz, Gilad Kuperman, Hannah Park, Alex Reyentovich, Stuart Katz
2017 Journal of Cardiac Failure
PDF DOI

Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network

Juan M. Banda, Yoni Halpern, David Sontag, Nigam H. Shah
2017 Proceedings of the AMIA Summit on Clinical Research Informatics (CRI)
PDF

Estimating individual treatment effect: generalization bounds and algorithms

Uri Shalit, Fredrik D. Johansson, David Sontag
2017 Proceedings of the 34th International Conference on Machine Learning
PDF

Grounded Recurrent Neural Networks

A. Vani, Y. Jernite, D. Sontag
2017 ArXiv e-prints arXiv:1705.08557
PDF

Learning a Health Knowledge Graph from Electronic Medical Records

Maya Rotmensch, Yoni Halpern, Abdulhakim Tlimat, Steven Horng, David Sontag
2017 Nature Scientific Reports
PDF

Objective Assessment of Depressive Symptoms with Machine Learning and Wearable Sensors Data

Asma Ghandeharioun, Szymon Fedor, Lisa Sangermano, Dawn Ionescu, Jonathan Alpert, Chelsea Dale, David Sontag, Rosalind Picard
2017 Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)
PDF

Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation

Yacine Jernite, Anna Choromanska, David Sontag
2017 Proceedings of the 34th International Conference on Machine Learning
PDF

Structured Inference Networks for Nonlinear State Space Models

Rahul G. Krishnan, Uri Shalit, David Sontag
2017 Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence
PDF

Using Machine Learning to Recommend Oncology Clinical Trials

Anasuya Das, Leifur Thorbergsson, Aleksandr Grigorenko, David Sontag, Iker Huerga
2017 Machine Learning for Health Care (Clinical abstract)
PDF

Character-Aware Neural Language Models

Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush
2016 Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence
PDF

Clinical Tagging with Joint Probabilistic Models

Yoni Halpern, Steven Horng, David Sontag
2016 Proceedings of the 1st Machine Learning for Healthcare Conference
PDF

Comparison of approaches for heart failure case identification from electronic health record data

Saul Blecker, Stuart Katz, LI Horwitz, Gilad Kuperman, H Park, A Gold, David Sontag
2016 JAMA Cardiology
PDF

Electronic Medical Record Phenotyping using the Anchor & Learn Framework

Yoni Halpern, Steven Horng, Youngduck Choi, David Sontag
2016 Journal of the American Medical Informatics Association (JAMIA)
PDF

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization

Shalmali Joshi, Suriya Gunasekar, David Sontag, Ghosh Joydeep
2016 Proceedings of the 1st Machine Learning for Healthcare Conference
PDF

Learning Low-Dimensional Representations of Medical Concepts

Youngduck Choi, Yi-I Chiu, David Sontag
2016 Proceedings of the AMIA Summit on Clinical Research Informatics (CRI)
PDF

Learning Representations for Counterfactual Inference

Fredrik Johansson, Uri Shalit, David Sontag
2016 Proceedings of The 33rd International Conference on Machine Learning
PDF

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests

Narges Razavian, Jake Marcus, David Sontag
2016 Proceedings of the 1st Machine Learning for Healthcare Conference
PDF

PhD Thesis: Semi-Supervised Learning for Electronic Phenotyping in Support of Precision Medicine

Yoni Halpern
2016
PDF

Population-Level Prediction of Type 2 Diabetes using Claims Data and Analysis of Risk Factors

Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, David Sontag
2016 Big Data
PDF

Tightness of LP Relaxations for Almost Balanced Models

Adrian Weller, Mark Rowland, David Sontag
2016 Proceedings of the 19th International Conference on Artificial Intelligence and Statistics
PDF

Train and Test Tightness of LP Relaxations in Structured Prediction

Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David Sontag
2016 Proceedings of The 33rd International Conference on Machine Learning
PDF

A Fast Variational Approach for Learning Markov Random Field Language Models

Yacine Jernite, Alexander Rush, David Sontag
2015 Proceedings of the 32nd International Conference on Machine Learning (ICML)
PDF

Anchored Discrete Factor Analysis

Yoni Halpern, Steven Horng, David Sontag
2015 arXiv preprint arXiv:1511.03299
PDF

Barrier Frank-Wolfe for Marginal Inference

Rahul G. Krishnan, Simon Lacoste-Julien, David Sontag
2015 Proceedings of the 28th International Conference on Neural Information Processing Systems
PDF

Deep Kalman Filters

Rahul G. Krishnan, Uri Shalit, David Sontag
2015 arXiv preprint arXiv:1511.05121
PDF

How Hard is Inference for Structured Prediction?

Amir Globerson, Tim Roughgarden, David Sontag, Cafer Yildirim
2015 Proceedings of the 32nd International Conference on Machine Learning (ICML)
PDF

PhD Thesis: Reasoning about Object Instances, Relations and Extents in RGBD Scenes

Nathan Silberman
2015
PDF

Predicting chronic comorbid conditions of type 2 diabetes in Newly-Diagnosed Diabetic Patients

N. Razavian, A. Smith-McLallen, S. Nigam, S. Blecker, A. M. Schmidt, D. Sontag
2015 Value in Health (Abstract)
PDF

Temporal Convolutional Neural Networks for Diagnosis from Lab Tests

Narges Razavian, David Sontag
2015 arXiv preprint arXiv:1511.07938
PDF

Visual Exploration of Temporal Data in Electronic Medical Records

Josua Krause, Narges Razavian, Enrico Bertini, David Sontag
2015 Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium (Abstract)
PDF

Instance Segmentation of Indoor Scenes using a Coverage Loss

Nathan Silberman, David Sontag, Rob Fergus
2014 Proceedings of the 13th European Conference on Computer Vision (ECCV)
PDF

Lifted Tree-Reweighted Variational Inference

Hung Hai Bui, Tuyen N. Huynh, David Sontag
2014 Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI-14)
PDF

Understanding the Bethe Approximation: When and How can it go Wrong?

Adrian Weller, Kui Tang, David Sontag, Tony Jebara
2014 Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI-14)
PDF

Unsupervised Learning of Disease Progression Models

Xiang Wang, David Sontag, Fei Wang
2014 Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PDF

Using Anchors to Estimate Clinical State without Labeled Data

Yoni Halpern, Youngduck Choi, Steven Horng, David Sontag
2014 Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium
PDF

A Practical Algorithm for Topic Modeling with Provable Guarantees

Sanjeev Arora, Rong Ge, Yoni Halpern, David M. Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu
2013 Proceedings of the International Conference on Machine Learning (ICML)
PDF

Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests

Yacine Jernite, Yoni Halpern, David Sontag
2013 Advances in Neural Information Processing Systems 26
PDF

Predicting Chief Complaints at Triage Time in the Emergency Department

Yacine Jernite, Yoni Halpern, Steven Horng, David Sontag
2013 NeurIPS Workshop on Machine Learning for Clinical Data Analysis and Healthcare
PDF

SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure

Eliot Brenner, David Sontag
2013 Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI-13)
PDF

Unsupervised Learning of Noisy-Or Bayesian Networks

Yoni Halpern, David Sontag
2013 Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI-13)
PDF

A Comparison of Dimensionality Reduction Techniques for Unstructured Clinical Text

Yoni Halpern, Steven Horng, Larry A. Nathanson, Nathan I. Shapiro, David Sontag
2012 ICML 2012 Workshop on Clinical Data Analysis
PDF

Efficiently Searching for Frustrated Cycles in MAP Inference

David Sontag, Do Kook Choe, Yitao Li
2012 Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI-12)
PDF

Introduction to Dual Decomposition for Inference

David Sontag, Amir Globerson, Tommi Jaakkola
2012 Optimization for Machine Learning
PDF

Probabilistic models for personalizing web search

David Sontag, Kevyn Collins-Thompson, Paul N. Bennett, Ryen W. White, Susan Dumais, Bodo Billerbeck
2012 Proceedings of the Fifth ACM International Conference on Web Search and Data Mining
PDF DOI

Complexity of Inference in Latent Dirichlet Allocation

David Sontag, Dan Roy
2011 Advances in Neural Information Processing Systems 24
PDF

Personalizing web search results by reading level

Kevyn Collins-Thompson, Paul N. Bennett, Ryen W. White, Sebastian de la Chica, David Sontag
2011 Proceedings of the 20th ACM International Conference on Information and Knowledge Management
PDF DOI

Dual Decomposition for Parsing with Non-Projective Head Automata

Terry Koo, Alexander M. Rush, Michael Collins, Tommi Jaakkola, David Sontag
2010 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF

Learning Bayesian Network Structure using LP Relaxations

Tommi Jaakkola, David Sontag, Amir Globerson, Marina Meila
2010 Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AI-STATS)
PDF

Learning Efficiently with Approximate Inference via Dual Losses

Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Globerson
2010 Proceedings of the 27th International Conference on Machine Learning (ICML)
PDF

More data means less inference: A pseudo-max approach to structured learning

David Sontag, Ofer Meshi, Tommi Jaakkola, Amir Globerson
2010 Advances in Neural Information Processing Systems 23
PDF

On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing

Alexander M. Rush, David Sontag, Michael Collins, Tommi Jaakkola
2010 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF

PhD Thesis: Approximate Inference in Graphical Models using LP Relaxations

David Sontag
2010
PDF

Clusters and Coarse Partitions in LP Relaxations

David Sontag, Amir Globerson, Tommi Jaakkola
2009 Advances in Neural Information Processing Systems 21
PDF

Scaling All-Pairs Overlay Routing

David Sontag, Yang Zhang, Amar Phanishayee, David Andersen, David Karger
2009 CoNEXT ‘09: Proceedings of the 5th international conference on Emerging networking experiments and technologies
PDF DOI

Tree Block Coordinate Descent for MAP in Graphical Models

David Sontag, Tommi Jaakkola
2009 Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AI-STATS)
PDF

New Outer Bounds on the Marginal Polytope

David Sontag, Tommi Jaakkola
2008 Advances in Neural Information Processing Systems 20
PDF

Tightening LP Relaxations for MAP using Message-Passing

David Sontag, Talya Meltzer, Amir Globerson, Yair Weiss, Tommi Jaakkola
2008 24th Conference on Uncertainty in Artificial Intelligence
PDF

Master’s Thesis: Cutting Plane Algorithms for Variational Inference in Graphical Models

David Sontag
2007
PDF

Probabilistic Modeling of Systematic Errors in Two-Hybrid Experiments

David Sontag, Rohit Singh, Bonnie Berger
2007 Pacific Symposium on Biocomputing
PDF

Approximate Inference for Infinite Contingent Bayesian Networks

Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
2005 Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics
PDF

BLOG: probabilistic models with unknown objects

Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
2005 IJCAI'05: Proceedings of the 19th international joint conference on Artificial intelligence
PDF