2 citations · 2 across the 5 of their papers we have counts for
5 papers
Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection
Chaimae Abouzahir, Musa Khan, Hala Ali-Hassan +7
Large Language Models (LLMs) perform strongly in English medical tasks but degrade substantially in Arabic, a gap widely attributed to limited training data. We systematically inve…
MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction
Congbo Ma, Hu Wang, Yichun Zhang +1
As Large Language Models (LLMs) are increasingly deployed in healthcare settings, accurate error detection and correction in generated or existing text becomes critical, as even mi…
MedErrBench: A Fine-Grained Multilingual Benchmark for Medical Error Detection and Correction with Clinical Expert Annotations
Congbo Ma, Yichun Zhang, Yousef Al-Jazzazi +6
Inaccuracies in existing or generated clinical text may lead to serious adverse consequences, especially if it is a misdiagnosis or incorrect treatment suggestion. With Large Langu…
Cross-Lingual Empirical Evaluation of Large Language Models for Arabic Medical Tasks
Chaimae Abouzahir, Congbo Ma, Nizar Habash +1
In recent years, Large Language Models (LLMs) have become widely used in medical applications, such as clinical decision support, medical education, and medical question answering.…
Uncertainty Quantification for Machine Learning in Healthcare: A Survey
L. Julián Lechuga López, Shaza Elsharief, Dhiyaa Al Jorf +3
Uncertainty Quantification (UQ) is pivotal in enhancing the robustness, reliability, and interpretability of Machine Learning (ML) systems for healthcare, optimizing resources and…