26 citations · 37 across the 7 of their papers we have counts for
4 papers · 1 filter
Machine-Learned Interatomic Potential for the Mo-S-Al-O System
Emir Bilgili, Nicholas Taormina, Simon R. Phillpot +1
We develop a machine-learned neuroevolution potential (NEP) for the Mo-S-Al-O system, targeting MoS heteroepitaxy on c-plane sapphire, -AlO(0001). The potential is t…
ViSTA: A Simple Bridge Extends Visual Alignment to Clinical Time-Series Understanding in Multimodal LLMs
Junyi Gao, Yu Shi, Pingzhao Hu +1
Clinical prediction models estimate risk from patient measurements, while large language models support medical text understanding and question answering. Yet their language capabi…
Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies
Junyu Yan, Damian Machlanski, Kurt Butler +4
Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to design optimally by hand when te…
Augmenting Clinical Decision-Making with an Interactive and Interpretable AI Copilot: A Real-World User Study with Clinicians in Nephrology and Obstetrics
Yinghao Zhu, Dehao Sui, Zixiang Wang +13
Clinician skepticism toward opaque AI hinders adoption in high-stakes healthcare. We present AICare, an interactive and interpretable AI copilot for collaborative clinical decision…