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…
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…
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…