40 citations · 53 across the 15 of their papers we have counts for
16 papers
Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats
Ee Wei Seah, Yongsen Zheng, Naga Nikshith +67
The rapid rise of autonomous AI systems and advancements in agent capabilities are introducing new risks due to reduced oversight of real-world interactions. Yet agent testing rema…
Machine Learning for Health symposium 2024 -- Findings track
Stefan Hegselmann, Helen Zhou, Elizabeth Healey +6
A collection of the accepted Findings papers that were presented at the 4th Machine Learning for Health symposium (ML4H 2024), which was held on December 15-16, 2024, in Vancouver,…
Learning to Route LLMs with Confidence Tokens
Yu-Neng Chuang, Prathusha Kameswara Sarma, Parikshit Gopalan +4
Large language models (LLMs) have demonstrated impressive performance on several tasks and are increasingly deployed in real-world applications. However, especially in high-stakes…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
MoCo-Transfer: Investigating out-of-distribution contrastive learning for limited-data domains
Yuwen Chen, Helen Zhou, Zachary C. Lipton
Medical imaging data is often siloed within hospitals, limiting the amount of data available for specialized model development. With limited in-domain data, one might hope to lever…
Business Metric-Aware Forecasting for Inventory Management
Helen Zhou, Sercan O. Arik, Jingtao Wang
Time-series forecasts play a critical role in business planning. However, forecasters typically optimize objectives that are agnostic to downstream business goals and thus can prod…
Evaluating Model Performance in Medical Datasets Over Time
Helen Zhou, Yuwen Chen, Zachary C. Lipton
Machine learning (ML) models deployed in healthcare systems must face data drawn from continually evolving environments. However, researchers proposing such models typically evalua…
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics
Shu Hu, George H. Chen
We propose a general approach for training survival analysis models that minimizes a worst-case error across all subpopulations that are large enough (occurring with at least a use…
Model Evaluation in Medical Datasets Over Time
Helen Zhou, Yuwen Chen, Zachary C. Lipton
Machine learning models deployed in healthcare systems face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in…
Domain Adaptation under Missingness Shift
Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton
Rates of missing data often depend on record-keeping policies and thus may change across times and locations, even when the underlying features are comparatively stable. In this pa…
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19
Helen Zhou, Cheng Cheng, Kelly J. Shields +4
With COVID-19 now pervasive, identification of high-risk individuals is crucial. Using data from a major healthcare provider in Southwestern Pennsylvania, we develop survival model…
Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data
Cheng Cheng, Helen Zhou, Jeremy C. Weiss +1
Since the COVID-19 pandemic first reached the United States, the case fatality rate has fallen precipitously. Several possible explanations have been floated, including greater det…
Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planning
Helen Zhou, Cheng Cheng, Zachary C. Lipton +2
Respiratory complications due to coronavirus disease COVID-19 have claimed tens of thousands of lives in 2020. Many cases of COVID-19 escalate from Severe Acute Respiratory Syndrom…
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
Soorajnath Boominathan, Michael Oberst, Helen Zhou +2
In several medical decision-making problems, such as antibiotic prescription, laboratory testing can provide precise indications for how a patient will respond to different treatme…
Digital Stylometry: Linking Profiles Across Social Networks
Soroush Vosoughi, Helen Zhou, Deb Roy
There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profi…
Enhanced Twitter Sentiment Classification Using Contextual Information
Soroush Vosoughi, Helen Zhou, Deb Roy
The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on twe…