5 papers
Contrastive Learning for Multi Label ECG Classification with Jaccard Score Based Sigmoid Loss
Junichiro Takahashi, Masataka Sato, Satoshi Kodeta +1
Recent advances in large language models (LLMs) have enabled the development of multimodal medical AI. While models such as MedGemini achieve high accuracy on VQA tasks like USMLE…
Transcoder-based Circuit Analysis for Interpretable Single-Cell Foundation Models
Sosuke Hosokawa, Toshiharu Kawakami, Satoshi Kodera +2
Single-cell foundation models (scFMs) have demonstrated state-of-the-art performance on various tasks, such as cell-type annotation and perturbation response prediction, by learnin…
CAG-VLM: Fine-Tuning of a Large-Scale Model to Recognize Angiographic Images for Next-Generation Diagnostic Systems
Yuto Nakamura, Satoshi Kodera, Haruki Settai +7
Coronary angiography (CAG) is the gold-standard imaging modality for evaluating coronary artery disease, but its interpretation and subsequent treatment planning rely heavily on ex…
Application of Contrastive Learning on ECG Data: Evaluating Performance in Japanese and Classification with Around 100 Labels
Junichiro Takahashi, JingChuan Guan, Masataka Sato +5
The electrocardiogram (ECG) is a fundamental tool in cardiovascular diagnostics due to its powerful and non-invasive nature. One of the most critical usages is to determine whether…
Video CLIP Model for Multi-View Echocardiography Interpretation
Ryo Takizawa, Satoshi Kodera, Tempei Kabayama +5
Echocardiography records ultrasound videos of the heart, enabling clinicians to assess cardiac function. Recent advances in large-scale vision-language models (VLMs) have spurred i…