aihealthx Goto Github PK
Name: AI - Healthcare
Type: Organization
Bio: AI in Healthcare, Imaging, EHR, Wearables, Labs, Drugs, Monitoring
Blog: aihealthx.github.io
Name: AI - Healthcare
Type: Organization
Bio: AI in Healthcare, Imaging, EHR, Wearables, Labs, Drugs, Monitoring
Blog: aihealthx.github.io
2D Image AI for Healthcare
3D Image Review AI for Healthcare
Unsupervised Domain Adaptation (AX2SAX) for CMR images, Koehler et al. 2021, IEEE TMI
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)
Deep learning cardiac segmentation and motion tracking
Implementation of the latest developments in NLP ranging from ensemble learning to BERT. Pipelines are in Tensorflow and Pytorch
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.
AI-Health web repo
2D CNN to classify different types of arrhythmia from ECG Signals
Awesome resources for artificial intelligence in cardiology
Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Data and codes for BioBERT-MRC
"I am going to hunt you down with science."― Steven Magee
cardiovascular_heart_disease
Cardiovascular Disease data set with 70,000 records of patients data, 11 features + target.
Cardiac Image Multi-Atlas Segmentation pipeline (CIMAS)
Predicting cardiovascular heart disease using CNN
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')
Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai
A Neo4j-GraphQL API for the CovidGraph project
R package for Cardiovascular Risk Dataset and Data generation script
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
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.
Documentation
A knowledge graph and a set of tools for drug repurposing
ECG Arrhythmia classification using CNN
This is the repository containing the MRI files and scripts used to analysed the data
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.