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A list of Medical imaging datasets.

OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

Methods and thoughts on defining geographic markets for health care services, i.e., a guided tour of a particularly complex rabbit hole.

Med-BERT, contextualized embedding model for structured EHR data

Data programming by demonstration for information extraction and span annotation

Framework for weakly supervised deep sequence taggers, focused on named entity recognition

Robustness Gym is an evaluation toolkit for machine learning.

Machine Learning for Information Retrieval

Official Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain

Search with BERT vectors in Solr, Elasticsearch, OpenSearch and GSI APU

This repository provides the implementation for the paper "Combining Fact Extraction and Verification with Neural Semantic Matching Networks".

🤖 A Python library for learning and evaluating knowledge graph embeddings

Oscar and VinVL

Source code for ACL 2019 paper "GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification"

BERT for Evidence Retrieval and Claim Verification

multilabel classification of EHR notes

An open source library for deep learning end-to-end dialog systems and chatbots.

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

A complete computer science study plan to become a software engineer.

Codes for publication "Two-stage Federated Phenotyping and Patient Representation Learning" Liu et al 2019

An open-source framework for machine learning and other computations on decentralized data.

ICD-10 codes classification with BERT and other models for CLEF eHealth Task 1

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Practice your pandas skills!

Text classification using different neural networks (CNN, LSTM, Bi-LSTM, C-LSTM).

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Automatic classification of medical patient discharge notes into standard disease labels, using deep learning models