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[JAMA] "Complete AI-Enabled Echocardiography Interpretation with Multitask Deep Learning" by Gregory Holste, Evangelos K. Oikonomou, Márton Tokodi, Attila Kovács, Zhangyang Wang, & Rohan Khera
A collection of projects and libraries to help implement FHIR-based products and solutions.
Create "Table 1" for research papers in Python
OpenMedCalc is a free, open-source medical calculation API
[NeurIPS 2024 Datasets and Benchmark Track Oral] MedCalc-Bench: Evaluating Large Language Models for Medical Calculations
Python workflow for generating benchmark datasets and machine learning models from the MIMIC-IV-ED database.
Python bindings and scikit-learn interface for the Operon library for symbolic regression.
Official repository for EchoFM: Foundation Model for Generalizable Echocardiogram Analysis
A benchmark of mortality risk prediction models using electrocardiograms.
A self-supervised foundation ECG model for broad and scalable cardiac applications
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
A collection of deep learning models for ECG data processing based on fairseq framework
[ICML 2021] Self-supervised pre-training of AI models on ECG data with CLOCS
PyTorch implementations of neural networks for timeseries classification
Benchmark time series data sets for PyTorch
An electrocardiogram analysis foundation model.
DSPy: The framework for programming—not prompting—language models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A guidance language for controlling large language models.
Singularity has been renamed to Apptainer as part of us moving the project to the Linux Foundation. This repo has been persisted as a snapshot right before the changes.