papers

Publications (8)

cs.CY2025

Safety challenges of AI in medicine in the era of large language models

Xiaoye Wang, Nicole Xi Zhang, Hongyu He +9

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have unlocked significant potential to enhance the quality and efficiency of medi…

cs.CV2025

DeepAf: One-Shot Spatiospectral Auto-Focus Model for Digital Pathology

Yousef Yeganeh, Maximilian Frantzen, Michael Lee +3

While Whole Slide Imaging (WSI) scanners remain the gold standard for digitizing pathology samples, their high cost limits accessibility in many healthcare settings. Other low-cost…

cs.CE2026

Computational Pathology in the Era of Emerging Foundation and Agentic AI -- International Expert Perspectives on Clinical Integration and Translational Readiness

Qian Da, Yijiang Chen, Min Ju +25

Recent breakthroughs in artificial intelligence through foundation models and agents have accelerated the evolution of computational pathology. Demonstrated performance gains repor…

cs.CV2026

RadGame: An AI-Powered Platform for Radiology Education

Mohammed Baharoon, Siavash Raissi, John S. Jun +29

We introduce RadGame, an AI-powered gamified platform for radiology education that targets two core skills: localizing findings and generating reports. Traditional radiology traini…

cs.CY2026

AI-generated data contamination erodes pathological variability and diagnostic reliability

Hongyu He, Shaowen Xiang, Ye Zhang +15

Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are increasingly at risk of train…

q-bio.OT2021

Ten Quick Tips for Deep Learning in Biology

Benjamin D. Lee, Anthony Gitter, Casey S. Greene +17

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that…

cs.CL2026

Human-in-the-Loop Large Language Model Framework for Identification of Cutaneous Immune-Related Adverse Events

Charles Lu, Olivia Burke, Debby Cheng +14

This study evaluated a retrieval-augmented, multi-agent large language model (LLM)-driven, human-in-the-loop framework for detecting cutaneous immune-related adverse events (cirAEs…

cs.AI2023

Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data

Dianbo Liu, Karmel W. Choi, Paulo Lizano +4

Importance: The prevalence of severe mental illnesses (SMIs) in the United States is approximately 3% of the whole population. The ability to conduct risk screening of SMIs at larg…