8 citations · 18 across the 7 of their papers we have counts for
7 papers
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging
Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra +5
For medical imaging AI models to be clinically impactful, they must generalize. However, this goal is hindered by (i) diverse types of distribution shifts, such as temporal, demogr…
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks
Jack Gallifant, Shan Chen, Pedro Moreira +7
Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases. This is particularly crucia…
Multi-State Brain Network Discovery
Hang Yin, Yao Su, Xinyue Liu +3
Brain network discovery aims to find nodes and edges from the spatio-temporal signals obtained by neuroimaging data, such as fMRI scans of human brains. Existing methods tend to de…
Continuous Time Evidential Distributions for Irregular Time Series
Taylor W. Killian, Haoran Zhang, Thomas Hartvigsen +1
Prevalent in many real-world settings such as healthcare, irregular time series are challenging to formulate predictions from. It is difficult to infer the value of a feature at an…
Interpretable Unified Language Checking
Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang +7
Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-…
Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks
Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong +1
Irregularly-sampled time series (ITS) are native to high-impact domains like healthcare, where measurements are collected over time at uneven intervals. However, for many classific…