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08/09/2023
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals
Heart failure is a debilitating condition that affects millions of peopl...
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08/03/2023
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception
AI alignment refers to models acting towards human-intended goals, prefe...
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07/26/2023
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data
Advances in large language models (LLMs) have empowered a variety of app...
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05/22/2023
Evaluating the Impact of Social Determinants on Health Prediction
Social determinants of health (SDOH) – the conditions in which people li...
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05/18/2023
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
Data sharing is crucial for open science and reproducible research, but ...
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02/23/2023
Change is Hard: A Closer Look at Subpopulation Shift
Machine learning models often perform poorly on subgroups that are under...
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01/13/2023
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning
In safety-critical decision-making scenarios being able to identify wors...
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11/20/2022
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Large pre-trained models decay over long-term deployment as input distri...
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10/19/2022
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Performance of machine learning models may differ between training and d...
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09/12/2022
If Influence Functions are the Answer, Then What is the Question?
Influence functions efficiently estimate the effect of removing a single...
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07/05/2022
Predicting Out-of-Domain Generalization with Local Manifold Smoothness
Understanding how machine learning models generalize to new environments...
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06/04/2022
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction
The standard approach to personalization in machine learning consists of...
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05/08/2022
Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations
Clinical notes are becoming an increasingly important data source for ma...
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05/06/2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Machine learning models in safety-critical settings like healthcare are ...
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03/23/2022
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning
Deep metric learning (DML) enables learning with less supervision throug...
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03/23/2022
Improving the Fairness of Chest X-ray Classifiers
Deep learning models have reached or surpassed human-level performance i...
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03/17/2022
Semi-Markov Offline Reinforcement Learning for Healthcare
Reinforcement learning (RL) tasks are typically framed as Markov Decisio...
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12/02/2021
Learning Optimal Predictive Checklists
Checklists are simple decision aids that are often used to promote safet...
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10/17/2021
Quantifying the Task-Specific Information in Text-Based Classifications
Recently, neural natural language models have attained state-of-the-art ...
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10/08/2021
Medical Dead-ends and Learning to Identify High-risk States and Treatments
Machine learning has successfully framed many sequential decision making...
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08/27/2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing
Machine learning models achieve state-of-the-art performance on many sup...
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08/27/2021
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations
Predictive models for clinical outcomes that are accurate on average in ...
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07/21/2021
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Background: In medical imaging, prior studies have demonstrated disparat...
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07/20/2021
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning
Deep Metric Learning (DML) aims to find representations suitable for zer...
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03/20/2021
An Empirical Framework for Domain Generalization in Clinical Settings
Clinical machine learning models experience significantly degraded perfo...
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11/23/2020
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
Reinforcement Learning (RL) has recently been applied to sequential esti...
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11/17/2020
Confounding Feature Acquisition for Causal Effect Estimation
Reliable treatment effect estimation from observational data depends on ...
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10/30/2020
Improving Dialogue Breakdown Detection with Semi-Supervised Learning
Building user trust in dialogue agents requires smooth and consistent di...
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10/29/2020
Multiple Sclerosis Severity Classification From Clinical Text
Multiple Sclerosis (MS) is a chronic, inflammatory and degenerative neur...
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10/13/2020
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings
Machine learning models in health care are often deployed in settings wh...
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09/23/2020
Probabilistic Machine Learning for Healthcare
Machine learning can be used to make sense of healthcare data. Probabili...
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09/22/2020
Ethical Machine Learning in Health Care
The use of machine learning (ML) in health care raises numerous ethical ...
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09/21/2020
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness
Models that perform well on a training domain often fail to generalize t...
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09/17/2020
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Deep Metric Learning (DML) provides a crucial tool for visual similarity...
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07/20/2020
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data
Multi-task learning (MTL) is a machine learning technique aiming to impr...
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06/26/2020
CheXpert++: Approximating the CheXpert labeler for Speed,Differentiability, and Probabilistic Output
It is often infeasible or impossible to obtain ground truth labels for m...
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06/22/2020
COVID-19 Image Data Collection: Prospective Predictions Are the Future
Across the world's coronavirus disease 2019 (COVID-19) hot spots, the ne...
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06/20/2020
Counterfactually Guided Policy Transfer in Clinical Settings
Reliably transferring treatment policies learned in one clinical environ...
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05/24/2020
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning
The need to streamline patient management for COVID-19 has become more p...
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03/11/2020
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
In this work, we examine the extent to which embeddings may encode margi...
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02/14/2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers
Machine learning systems have received much attention recently for their...
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08/02/2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
When training clinical prediction models from electronic health records ...
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07/19/2019
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Robust machine learning relies on access to data that can be used with s...
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07/02/2019
Reproducibility in Machine Learning for Health
Machine learning algorithms designed to characterize, monitor, and inter...
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04/04/2019
Clinically Accurate Chest X-Ray Report Generation
The automatic generation of radiology reports given medical radiographs ...
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11/30/2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation
Machine learning for healthcare often trains models on de-identified dat...
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11/29/2018
The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech
Speech datasets for identifying Alzheimer's disease (AD) are generally r...
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11/17/2018
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
This volume represents the accepted submissions from the Machine Learnin...
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10/13/2018
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation
Making decisions about what clinical tasks to prepare for is multi-facto...
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08/11/2018
