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08/09/2023
Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes
The large amount of time clinicians spend sifting through patient notes ...
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05/26/2023
Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration
Health insurers often use algorithms to identify members who would benef...
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05/08/2023
Large-Scale Study of Temporal Shift in Health Insurance Claims
Most machine learning models for predicting clinical outcomes are develo...
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04/05/2023
Beyond Summarization: Designing AI Support for Real-World Expository Writing Tasks
Large language models have introduced exciting new opportunities and cha...
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04/04/2023
Conformalized Unconditional Quantile Regression
We develop a predictive inference procedure that combines conformal pred...
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01/30/2023
Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions
Randomized Controlled Trials (RCT)s are relied upon to assess new treatm...
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01/15/2023
Who Should Predict? Exact Algorithms For Learning to Defer to Humans
Automated AI classifiers should be able to defer the prediction to a hum...
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10/19/2022
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
We study the application of large language models to zero-shot and few-s...
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09/27/2022
Falsification before Extrapolation in Causal Effect Estimation
Randomized Controlled Trials (RCTs) represent a gold standard when devel...
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07/19/2022
Sample Efficient Learning of Predictors that Complement Humans
One of the goals of learning algorithms is to complement and reduce the ...
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06/06/2022
Training Subset Selection for Weak Supervision
Existing weak supervision approaches use all the data covered by weak si...
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05/31/2022
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
We give a method for proactively identifying small, plausible shifts in ...
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05/25/2022
Large Language Models are Zero-Shot Clinical Information Extractors
We show that large language models, such as GPT-3, perform well at zero-...
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05/21/2022
Bias-robust Integration of Observational and Experimental Estimators
We describe a simple approach for combining an unbiased and a (possibly)...
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02/02/2022
Co-training Improves Prompt-based Learning for Large Language Models
We demonstrate that co-training (Blum Mitchell, 1998) can improve th...
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11/22/2021
Teaching Humans When To Defer to a Classifier via Exemplars
Expert decision makers are starting to rely on data-driven automated age...
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11/04/2021
Leveraging Time Irreversibility with Order-Contrastive Pre-training
Label-scarce, high-dimensional domains such as healthcare present a chal...
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10/28/2021
Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
We study prediction of future outcomes with supervised models that use p...
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10/27/2021
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
Individuals often make different decisions when faced with the same cont...
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09/23/2021
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records
Clinical documentation can be transformed by Electronic Health Records, ...
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06/04/2021
CLIP: A Dataset for Extracting Action Items for Physicians from Hospital Discharge Notes
Continuity of care is crucial to ensuring positive health outcomes for p...
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03/08/2021
Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative
Automated decision support can accelerate tedious tasks as users can foc...
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03/03/2021
Regularizing towards Causal Invariance: Linear Models with Proxies
We propose a method for learning linear models whose predictive performa...
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02/26/2021
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
Several works have shown that perturbation stable instances of the MAP i...
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02/22/2021
Neural Pharmacodynamic State Space Modeling
Modeling the time-series of high-dimensional, longitudinal data is impor...
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02/13/2021
Clustering Left-Censored Multivariate Time-Series
Unsupervised learning seeks to uncover patterns in data. However, differ...
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02/13/2021
Pulse of the Pandemic: Iterative Topic Filtering for Clinical Information Extraction from Social Media
The rapid evolution of the COVID-19 pandemic has underscored the need to...
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11/07/2020
Graph cuts always find a global optimum (with a catch)
We prove that the alpha-expansion algorithm for MAP inference always ret...
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10/08/2020
Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies
Treatment policies learned via reinforcement learning (RL) from observat...
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07/31/2020
Robust Benchmarking for Machine Learning of Clinical Entity Extraction
Clinical studies often require understanding elements of a patient's nar...
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07/29/2020
Fast, Structured Clinical Documentation via Contextual Autocomplete
We present a system that uses a learned autocompletion mechanism to faci...
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07/23/2020
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Data cleaning can be naturally framed as probabilistic inference in a ge...
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07/10/2020
Deep Contextual Clinical Prediction with Reverse Distillation
Healthcare providers are increasingly using learned methods to predict a...
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06/02/2020
Consistent Estimators for Learning to Defer to an Expert
Learning algorithms are often used in conjunction with expert decision m...
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06/01/2020
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
In several medical decision-making problems, such as antibiotic prescrip...
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04/27/2020
Knowledge Base Completion for Constructing Problem-Oriented Medical Records
Both electronic health records and personal health records are typically...
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01/21/2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Practitioners in diverse fields such as healthcare, economics and educat...
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10/10/2019
Estimation of Utility-Maximizing Bounds on Potential Outcomes
Estimation of individual treatment effects is often used as the basis fo...
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10/07/2019
Open Set Medical Diagnosis
Machine-learned diagnosis models have shown promise as medical aides but...
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10/02/2019
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph
Increasingly large electronic health records (EHRs) provide an opportuni...
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07/09/2019
Characterization of Overlap in Observational Studies
Overlap between treatment groups is required for nonparametric estimatio...
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06/28/2019
Benefits of Overparameterization in Single-Layer Latent Variable Generative Models
One of the most surprising and exciting discoveries in supervising learn...
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05/14/2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
We introduce an off-policy evaluation procedure for highlighting episode...
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03/08/2019
Support and Invertibility in Domain-Invariant Representations
Learning domain-invariant representations has become a popular approach ...
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01/24/2019
Overcomplete Independent Component Analysis via SDP
We present a novel algorithm for overcomplete independent components ana...
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11/07/2018
Prototypical Clustering Networks for Dermatological Disease Diagnosis
We consider the problem of image classification for the purpose of aidin...
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10/12/2018
Block Stability for MAP Inference
To understand the empirical success of approximate MAP inference, recent...
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05/31/2018
Evaluating Reinforcement Learning Algorithms in Observational Health Settings
Much attention has been devoted recently to the development of machine l...
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05/30/2018
Why Is My Classifier Discriminatory?
Recent attempts to achieve fairness in predictive models focus on the ba...
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02/23/2018