aihealthx Goto Github PK

2d-image-review

2D Image AI for Healthcare

3d-image-review

3D Image Review AI for Healthcare

3d-mri-domain-adaptation

Unsupervised Domain Adaptation (AX2SAX) for CMR images, Koehler et al. 2021, IEEE TMI

3d-ucaps

3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)

4dsegment

Deep learning cardiac segmentation and motion tracking

advanced-nlp

Implementation of the latest developments in NLP ranging from ensemble learning to BERT. Pipelines are in Tensorflow and Pytorch

ai-for-healthcare-nanodegree

Learn to build, evaluate, and integrate predictive models that have the power to transform patient outcomes. Begin by classifying and segmenting 2D and 3D medical images to augment diagnosis and then move on to modeling patient outcomes with electronic health records to optimize clinical trial testing decisions. Finally, build an algorithm that uses data collected from wearable devices to estimate the wearer’s pulse rate in the presence of motion.

aihealthx.github.io

AI-Health web repo

arrhythmia-cnn

2D CNN to classify different types of arrhythmia from ECG Signals

awesome-ai-cardiology

Awesome resources for artificial intelligence in cardiology

biobert

Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining

biobert-mrc

Data and codes for BioBERT-MRC

cardiology-ml-papers

"I am going to hunt you down with science."― Steven Magee

cardiovascular-risk-prediction

cardiovascular_heart_disease

cardiovascular_heart_disease

cardiovasculardiseaseclassification

Cardiovascular Disease data set with 70,000 records of patients data, 11 features + target.

cimas

Cardiac Image Multi-Atlas Segmentation pipeline (CIMAS)

cnn-cardioprediction

Predicting cardiovascular heart disease using CNN

compounddb4j

coronary-artery-tracking-via-3d-cnn-classification

The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')

coursera-ai-for-medicine-specialization

Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai

covid-graph-graphql

A Neo4j-GraphQL API for the CovidGraph project

cvdriskdata

R package for Cardiovascular Risk Dataset and Data generation script

dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

diagnostic-model-for-predicting-cardiovascular-disease-risk

The objective of this project is to develop computational algorithm that can accurately detect cardiovascular related diseases. The dataset used in this project was obtained from the publically available UCI repository heart disease dataset. This dataset has been considered the benchmark dataset in the computational cardiovascular space. The features used in the development of this model are considered medically relevant attributes(as indicated in the literature) as they significantly contribute to the progression of cardiovascular disease.

docs

Documentation

documentation

drkg

A knowledge graph and a set of tools for drug repurposing

ecg-classification

ECG Arrhythmia classification using CNN

entanglement-witnessed-in-the-human-brain

This is the repository containing the MRI files and scripts used to analysed the data