teamubuntu,github

ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

epimodel

Mathematical Modeling of Infectious Disease Dynamics

gossis

Extracting consistent concepts from multiple databases

healthcare_ml

A curated list of ML|NLP resources for healthcare.

heart-disease-analysis-and-prediction

Heart Disease Analysis repository

heart-disease-prediction

The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.

heart-disease-prediction-1

Various classification algorithms are implemented to predict whether a person is prone to or is suffering from heart disease

hetionet

Hetionet: an integrative network of disease

humandiseaseontology

Repository for the Human Disease Ontology.

mimic3-benchmarks

Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

pathogentransmissionontology

The Pathogen Transmission Ontology describes the tranmission methods of human disease pathogens describing how a pathogen is transmitted from one host, reservoir, or source to another host. The pathogen transmission may occur either directly or indirectly and may involve animate vectors or inanimate vehicles. The Pathogen Transmission Ontology is available under CC0 license (https://creativecommons.org/publicdomain/zero/1.0/).

predicting-diseases-from-symptoms

Training a decision tree to predict diseases from symptoms.

pyhealth

A Python Library for Healthcare AI

pytorch-flask-deploy-webapp

This is a Flask + Docker deployment of the PyTorch-based Named Entity Recognition (NER) Model (BiLSTM-CRF) in the Medical AI.

realworld

"The mother of all demo apps" — Exemplary fullstack Medium.com clone powered by React, Angular, Node, Django, and many more 🏅

scisumm-corpus

Scientific Document Summarization Corpus and Annotations from the WING NUS group.

symptom-disease

Finds out symptoms similar to a given symptom, from a symptom-disease data set.

symptomontology

The symptom ontology was designed around the guiding concept of a symptom being: “A perceived change in function, sensation or appearance reported by a patient indicative of a disease”. Understanding the close relationship of Signs and Symptoms, where Signs are the objective observation of an illness, the Symptom Ontology will work to broaden it’s scope to capture and document in a more robust manor these two sets of terms. Understanding that at times, the same term may be both a Sign and a Symptom. The Symptom Ontology is available under CC0 license (https://creativecommons.org/publicdomain/zero/1.0/).

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