Stars
Towards Predicting Temporal Changes in a Patient's Chest X-ray Images based on Electronic Health Records (CHIL 2025)
Official Implementations of "Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space""
Awesome-LLM-Tabular: a curated list of Large Language Model applied to Tabular Data
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.
Limited automatic tabular ML pipelines for generic MEDS datasets.
Metrics to evaluate quality and efficacy of synthetic datasets.
🧪Yet Another ICU Benchmark: a holistic framework for the standardization of clinical prediction model experiments. Provide custom datasets, cohorts, prediction tasks, endpoints, preprocessing, and …
MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases
A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.
Hands-on repository for fine-tuning Large Language Models (LLMs) in the clinical domain with tutorials
[NeurIPS 2024 D&B] Official code for "EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries"
[NeurIPS'22] EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records
Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records
Official implementation for the paper "A Cheaper and Better Diffusion Language Model with Soft-Masked Noise"
Machine Learning Engineering Open Book
Vector (and Scalar) Quantization, in Pytorch
A new collection of medical VQA dataset based on MIMIC-CXR. Part of the work 'EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images, NeurIPS 2023 D&B'.
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images, NeurIPS 2023 D&B
Perspective Projection-Based 3D CT Reconstruction from Biplanar X-rays (ICASSP 2023, Best Student Paper Awards)
Awesome-LLM: a curated list of Large Language Model
[MICCAI-2022] This is the official implementation of Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training.
A Deep Learning Python Toolkit for Healthcare Applications.