A deep learning model fine-tuned based on ResNet-50 for ECG image classification, assisting in cardiac disease detection

Computer VisionTensorflowEnglish

GEM is a multimodal large language model that integrates ECG time series, 12-lead ECG images, and text to enable clinical evidence-based ECG interpretation.

MultimodalTransformers

A self-supervised foundational model for broadly scalable cardiac applications, trained on 9.1 million 12-lead ECGs covering 164 cardiovascular diseases

Scientific ComputingTransformers

HuBERT - ECG is a basic model pre-trained through self-supervised learning on a large-scale and diverse electrocardiogram (ECG) dataset. It can be quickly fine-tuned and applied to various cardiovascular disease diagnosis and event prediction tasks by adding a simple output layer, demonstrating excellent performance and wide applicability.

Scientific ComputingTransformers

A self-supervised pre-trained foundation model for ECG analysis, supporting detection of 164 cardiovascular diseases

Scientific ComputingTransformers

A multimodal large language model (MLLM) specifically designed for interpreting electrocardiogram (ECG) images, capable of handling various ECG-related tasks from diverse data sources.

MultimodalSafetensorsEnglish

A deep learning model for generating synthetic ECG that creates realistic electrocardiogram data for medical research and development

Scientific ComputingTransformersEnglish