All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–8 of 8 filtered models
- National University of Singapore +1 otherMarch 8, 2025cardiologyclinical_reasoningdiagnosis_grounding+7
Multimodal LLM unifying 12-lead ECG time series, ECG images, and text for grounded, clinician-aligned electrocardiogram interpretation.
BiosignalsLanguage model79Openness ECG-LM
—33—A multimodal LLM that aligns a specialized ECG signal encoder with BioMedGPT-LM-7B for cardiovascular disease detection and ECG question answering.
BiosignalsLanguage model24OpennessECGFM-KED
4241—A knowledge-enhanced ECG foundation model that pairs a ResNet signal encoder with LLM-derived diagnostic knowledge for zero- and few-shot electrocardiogram interpretation.
Biosignals30OpennessPULSE
6427999A multimodal LLM fine-tuned to interpret electrocardiogram images, trained on the >1M-sample ECGInstruct dataset and evaluated on the ECGBench benchmark.
BiosignalsImaging84OpennessECGFounder
12432128A 1D convolutional foundation model for electrocardiogram analysis, trained on over 10 million expert-annotated recordings across 150 diagnostic categories.
Biosignals75OpennessECG-Chat
8044—China University of Geosciences +2 othersAugust 16, 2024cardiologycontrastive_learningdisease_classification+6A multimodal ECG-language model that aligns 12-lead ECG waveforms with clinical text for conversational cardiac diagnosis and automated report generation.
BiosignalsLanguage model27OpennessECG-FM
28887—An open transformer foundation model for 12-lead electrocardiograms, pretrained on 1.5M ECGs with hybrid contrastive and generative self-supervision.
Biosignals67OpennessHeartBEiT
25111—A BEiT vision transformer pretrained on 8.5M 12-lead ECG images via masked image modeling, excelling at low-data-regime cardiac diagnosis.
Biosignals30Openness