45 citations · 139 across the 18 of their papers we have counts for
23 papers
MammoExpert: Benchmarking Chain-of-Thought Reasoning in Mammography Diagnosis
Di Dai, Bo Liu, Youcheng Li +9
Mammography is an essential tool for breast cancer detection, with millions of examinations conducted annually. However, publicly available high-quality mammography datasets for AI…
CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts
Bo Liu, Di Dai, Jingwei Liu +5
Granger Causal Discovery (GCD) is fundamental for analyzing temporal dependencies in complex systems. However, existing neural GCD methods predominantly rely on a "one-size-fits-al…
Self-Alignment Learning to Improve Myocardial Infarction Detection from Single-Lead ECG
Jiarui Jin, Xiaocheng Fang, Haoyu Wang +5
Myocardial infarction is a critical manifestation of coronary artery disease, yet detecting it from single-lead electrocardiogram (ECG) remains challenging due to limited spatial i…
PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection
Xiaocheng Fang, Jiarui Jin, Haoyu Wang +8
Electrocardiography (ECG) is the clinical gold standard for cardiovascular disease (CVD) assessment, yet continuous monitoring is constrained by the need for dedicated hardware and…
Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model
Jiarui Jin, Haoyu Wang, Hongyan Li +3
Electrocardiogram (ECG) is essential for the clinical diagnosis of arrhythmias and other heart diseases, but deep learning methods based on ECG often face limitations due to the ne…
Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks
Chenxi Sun, Hongyan Li, Moxian Song +3
Continuous diagnosis and prognosis are essential for intensive care patients. It can provide more opportunities for timely treatment and rational resource allocation, especially fo…