4 citations · 6 across the 5 of their papers we have counts for
6 papers
Agentic AI Enhances Physician Trust in Clinical Decision Making
Zhiling Yan, Zhe Fang, David J King +10
Medical AI has shifted from reasoning to agentic AI, a new paradigm that autonomously invokes external tools during reasoning, rendering intermediate reasoning steps and tool outpu…
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
Juncheng Wu, Wenlong Deng, Xingxuan Li +12
Medical tasks such as diagnosis and treatment planning require precise and complex reasoning, particularly in life-critical domains. Unlike mathematical reasoning, medical reasonin…
EchoFM: Foundation Model for Generalizable Echocardiogram Analysis
Sekeun Kim, Pengfei Jin, Sifan Song +6
Foundation models have recently gained significant attention because of their generalizability and adaptability across multiple tasks and data distributions. Although medical found…
Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis
Sekeun Kim, Hui Ren, Peng Guo +5
Echocardiography segmentation for cardiac analysis is time-consuming and resource-intensive due to the variability in image quality and the necessity to process scans from various…
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training
Hongmin Cai, Wenxiong Liao, Zhengliang Liu +12
Modern supervised learning neural network models require a large amount of manually labeled data, which makes the construction of domain-specific knowledge graphs time-consuming an…