3 citations · 4 across the 4 of their papers we have counts for
5 papers
From Image Interpretation to Clinical Reasoning: Upstream Physician-Context-Aware Multimodal Learning with Causal Reinforcement Learning
Jialu Pi, Yanan Ma, Weijie Chen +8
Major adverse cardiovascular events (MACE) remain the leading cause of mortality worldwide. Opportunistic screening using routinely acquired clinical data offers a scalable approac…
MOSCARD -- Causal Reasoning and De-confounding for Multimodal Opportunistic Screening of Cardiovascular Adverse Events
Jialu Pi, Juan Maria Farina, Rimita Lahiri +7
Major Adverse Cardiovascular Events (MACE) remain the leading cause of mortality globally, as reported in the Global Disease Burden Study 2021. Opportunistic screening leverages da…
Multi-Analyte, Swab-based Automated Wound Monitor with AI
Madhu Babu Sikha, Lalith Appari, Gurudatt Nanjanagudu Ganesh +2
Diabetic foot ulcers (DFUs), a class of chronic wounds, affect ~750,000 individuals every year in the US alone and identifying non-healing DFUs that develop to chronic wounds early…
Benchmark on Peer Review Toxic Detection: A Challenging Task with a New Dataset
Man Luo, Bradley Peterson, Rafael Gan +5
Peer review is crucial for advancing and improving science through constructive criticism. However, toxic feedback can discourage authors and hinder scientific progress. This work…
Assessing Empathy in Large Language Models with Real-World Physician-Patient Interactions
Man Luo, Christopher J. Warren, Lu Cheng +2
The integration of Large Language Models (LLMs) into the healthcare domain has the potential to significantly enhance patient care and support through the development of empathetic…