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PKUDigitalHealth / ECGFounder
Forked from NickLJLee/ECGFounderThis is the official implementation of our paper "An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains".
Official Repository of "Learning to Reason under Off-Policy Guidance"
Code for the paper "ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?"
assistant tools for attention visualization in deep learning
[CVPR 2024 Extension] 160K volumes (42M slices) datasets, 31M-1.2B pre-trained models, various pre-training recipes, 50+ downstream tasks implementation
[ICLR 2025] MLLM for On-Demand Spatial-Temporal Understanding at Arbitrary Resolution
This is the official repository for the paper "3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers"
Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷
Official Repository of "Robust Detection Outcome: A Metric for Pathology Detection in Medical Images"
[ICML 2024] This repository includes the official implementation of our paper "Rejuvenating image-GPT as Strong Visual Representation Learners"
[ECCV 2024] Official PyTorch implementation of DreamLIP: Language-Image Pre-training with Long Captions
GPT4V-level open-source multi-modal model based on Llama3-8B
Autoregressive Model Beats Diffusion: 🦙 Llama for Scalable Image Generation
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
Official implementation of "Why are Visually-Grounded Language Models Bad at Image Classification?" (NeurIPS 2024)
The medical imaging meta-learning toolbox allows to build models that learn to learn in a setting with diverse tasks. It also provides code for working with the MIMeta Dataset as well as simple bas…
2D residual U-Net (ResUNet) and a lead combiner (LC) for 12-lead ECG Abnormality Classification
Accelerating the development of large multimodal models (LMMs) with one-click evaluation module - lmms-eval.
We present a comprehensive and deep review of the HFM in challenges, opportunities, and future directions. The released paper: https://arxiv.org/abs/2404.03264
Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)