All Competitors

Every biological foundation model, evaluated and ranked by the bio.rodeo team

Showing 1–4 of 4 filtered models

  • GEM (Grounded ECG understanding with Multimodal LLM)

    18837252
    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 model
    79Openness

  • ECG-LM

    —33—
    Tsinghua University +1 otherFebruary 4, 2025cardiologycardiovascular_disease_detectioncnn+6

    A multimodal LLM that aligns a specialized ECG signal encoder with BioMedGPT-LM-7B for cardiovascular disease detection and ECG question answering.

    BiosignalsLanguage model
    24Openness

  • PULSE

    6427999
    The Ohio State University +1 otherOctober 21, 2024cardiologyecgecg_interpretation+6

    A multimodal LLM fine-tuned to interpret electrocardiogram images, trained on the >1M-sample ECGInstruct dataset and evaluated on the ECGBench benchmark.

    BiosignalsImaging
    84Openness

  • ECG-FM

    28887—
    University of Toronto +1 otherAugust 9, 2024cardiologycontrastive_learningdisease_classification+6

    An open transformer foundation model for 12-lead electrocardiograms, pretrained on 1.5M ECGs with hybrid contrastive and generative self-supervision.

    Biosignals
    67Openness