activity
20202025
most citedWhat Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

64 citations · 67 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment

Pawel Renc, Michal K. Grzeszczyk, Linglong Qian +3

We present Federated Timeline Synthesis (FTS), a novel framework for training generative foundation models across distributed timeseries data applied to electronic health records (…

cs.LG2025

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation

Pawel Renc, Michal K. Grzeszczyk, Nassim Oufattole +9

Hospitals struggle to predict critical outcomes. Traditional early warning systems, like NEWS and MEWS, rely on static variables and fixed thresholds, limiting their adaptability,…

cs.LG2024★ 1 cited

MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets

Nassim Oufattole, Teya Bergamaschi, Aleksia Kolo +4

Effective, reliable, and scalable development of machine learning (ML) solutions for structured electronic health record (EHR) data requires the ability to reliably generate high-q…

cs.CV2024

LEMoN: Label Error Detection using Multimodal Neighbors

Haoran Zhang, Aparna Balagopalan, Nassim Oufattole +4

Large repositories of image-caption pairs are essential for the development of vision-language models. However, these datasets are often extracted from noisy data scraped from the…

cs.LG2023★ 2 cited

Event-Based Contrastive Learning for Medical Time Series

Hyewon Jeong, Nassim Oufattole, Matthew Mcdermott +4

In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event. For example, quantifying the risk of adverse o…

cs.LG2023

A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series

Anna Wong, Shu Ge, Nassim Oufattole +4

Sepsis is a life-threatening condition triggered by an extreme infection response. Our objective is to forecast sepsis patient outcomes using their medical history and treatments,…

cs.CL2020★ 64 cited

What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Di Jin, Eileen Pan, Nassim Oufattole +3

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present t…