240 citations · 254 across the 4 of their papers we have counts for
4 papers
MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
Suhana Bedi, Hejie Cui, Miguel Fuentes +78
While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…
Atlas Based Segmentations via Semi-Supervised Diffeomorphic Registrations
Charles Huang, Masoud Badiei, Hyunseok Seo +5
Purpose: Segmentation of organs-at-risk (OARs) is a bottleneck in current radiation oncology pipelines and is often time consuming and labor intensive. In this paper, we propose an…
A Scalable Discrete-Time Survival Model for Neural Networks
Michael F. Gensheimer, Balasubramanian Narasimhan
There is currently great interest in applying neural networks to prediction tasks in medicine. It is important for predictive models to be able to use survival data, where each pat…
Abstract: Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients
Imon Banerjee, Michael Francis Gensheimer, Douglas J. Wood +3
We propose a deep learning model - Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) for estimating short-term life expectancy (3 months) of t…