33 citations · 122 across the 12 of their papers we have counts for
6 papers · 1 filter
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
Michael Wornow, Rahul Thapa, Ethan Steinberg +2
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…
All models are local: time to replace external validation with recurrent local validation
Alex Youssef, Michael Pencina, Anshul Thakur +3
External validation is often recommended to ensure the generalizability of ML models. However, it neither guarantees generalizability nor equates to a model's clinical usefulness (…
The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs
Michael Wornow, Yizhe Xu, Rahul Thapa +6
The successes of foundation models such as ChatGPT and AlphaFold have spurred significant interest in building similar models for electronic medical records (EMRs) to improve patie…
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record
Conor K. Corbin, Rob Maclay, Aakash Acharya +6
Machine learning (ML) applications in healthcare are extensively researched, but successful translations to the bedside are scant. Healthcare institutions are establishing framewor…
MOTOR: A Time-To-Event Foundation Model For Structured Medical Records
Ethan Steinberg, Jason Fries, Yizhe Xu +1
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…
Instability in clinical risk stratification models using deep learning
Daniel Lopez-Martinez, Alex Yakubovich, Martin Seneviratne +9
While it has been well known in the ML community that deep learning models suffer from instability, the consequences for healthcare deployments are under characterised. We study th…