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Ethan Steinberg

6 accepted papers

2025

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data

ICLR 2025poster

Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art results on numerous clinical prediction tasks. However, prior EHR FMs typically have context windows of $<$1k tokens, which prevents them from modeling full patient EHRs which can exceed 10k's of event…

Cited by 1SourcePDFScholar
2025

Time-to-Event Pretraining for 3D Medical Imaging

ICLR 2025poster

With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predictive of future disease risk. While current self-supervised methods for 3D medical imaging models capture local structura…

2024

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records

ICLR 2024spotlight

We present a self-supervised, time-to-event (TTE) foundation model called MOTOR (Many Outcome Time Oriented Representations) which is pretrained on timestamped sequences of events in electronic health records (EHR) and health insurance claims. TTE models are used for estimating the probability distr…

Cited by 17SourcePDFScholar
2024

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

AAAI 2024technical

The ability of large language models (LLMs) to follow natural language instructions with human-level fluency suggests many opportunities in healthcare to reduce administrative burden and improve quality of care. However, evaluating LLMs on realistic text generation tasks for healthcare remains chall…

Cited by 67SourcePDFScholar
2023

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models

NeurIPS 2023spotlight

While the general machine learning (ML) community has benefited from public datasets, tasks, and models, the progress of ML in healthcare has been hampered by a lack of such shared assets. The success of foundation models creates new challenges for healthcare ML by requiring access to shared pretrai…

2023

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis

NeurIPS 2023poster

Synthesizing information from various data sources plays a crucial role in the practice of modern medicine. Current applications of artificial intelligence in medicine often focus on single-modality data due to a lack of publicly available, multimodal medical datasets. To address this limitation, we…

Cited by 11SourcePDFScholar