A curated list of awesome resources at the intersection of healthcare and AI.
Table of Contents generated with DocToc
- Awesome Healthmetrics *
- Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities - 2021
- Adversarial attacks on medical AI: A health policy challenge - 2019
- Transfusion: Understanding Transfer Learning with Applications to Medical Imaging - 2019
- High-performance medicine: the convergence of human and artificial intelligence - 2019
- Big data and machine learning in health care - 2018
- Opportunities in Machine Learning for Healthcare - 2018
- A Survey on Deep Learning in Medical Image Analysis - 2017
- Translating Artificial Intelligence Into Clinical Care - 2016
- Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
- The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age
- Awesome Healthcare
- healthcareai: R tools for healthcare machine learning
- Image Segmentation with Pytorch
- medpy: medical image processing in Python
- Grand Challenges in Biomedical Image Analysis
- Predict Blood Donations - DrivenData - open
- Countable Care: Modeling Women's Health Care Decisions - DrivenData - 2015
- Heritage Health Prize: Identify patients who will be admitted to a hospital within the next year using historical claims data - Kaggle - 2012
- Conference on Artificial Intelligence in Medicine
- Deep Learning in Healthcare Summit
- Machine Learning for Healthcare
- Getting to the Heart of it: How Deep Learning is Transforming Cardiac Imaging - 2018
- Artificial Intelligence in Cardiology - 2018
- Cardiac imaging: working towards fully-automated machine analysis & interpretation - 2017
- Cardiac MRI dataset
- Congenital Heart Disease (CHD)
- SPECT - Heart Dataset
- Stanford’s South African Heart Disease Dataset
- Sunnybrook Cardiac Data
- UCI - Heart Disease Dataset
- Machine Learning with a Heart: predicting heart disease - DrivenData - open
- II Annual Data Science Bowl: transforming how we diagnose heart disease - Kaggle - 2016
- Artificial Intelligence in Public Health and Epidemiology - 2018
- Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology - 2018
- Machine-learned epidemiology: real-time detection of foodborne illness at scale - 2018
- Machine learning spots treasure trove of elusive viruses
- Big Data for Infectious Disease Surveillance and Modeling
- Cancer Registration: Epidemiology of lung cancer tumours in England 2009 to 2013
- University Library: Epidemiology and Health Statistics
- DengAI: predicting disease spread - DrivenData - open
- Predict HIV Progression: predict the likelihood that an HIV patient's infection will become less severe, given a small dataset and limited clinical information - Kaggle - 2010
- West Nile Virus Prediction: predict West Nile virus in mosquitos across the city of Chicago - Kaggle - 2015
- A primer on deep learning in genomics - 2019
- Approximate Bayesian computation with deep learning supports a third archaic introgression in Asia and Oceania - 2019
- Machine learning applications in genetics and genomics - 2015
- Clinical Genomic Database
- Genotype-Tissue Expression
- Project Achilles
- The drug gene interaction database
- biopython: python tools for computational molecular biology
- pyGeno: personalized Genomics and Proteomics
- Gene Expression Prediction: Predicting gene expression from histone modification signals - Kaggle - 2017
- International Conference on Bioinformatics Research and Applications (ICBRA)
- International Symposium on Bioinformatics Research and Applications (ISBRA)
- Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks - Nature Medicine - 2020
- A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain - 2018
- High-precision automated reconstruction of neurons with flood-filling networks - 2018
- Machine learning in neurology: what neurologists can learn from machines and vice versa - 2018
- AI and Neuroscience: A virtuous circle
- Artificial Intelligence and Neurology - 2016
- Advanced Data Analysis in Neuroscience: Integrating Statistical and Computational Models
- Computational Neurology and Psychiatry
- Handbook of Functional MRI Data Analysis
- Neural Data Science: A Primer with MATLAB and Python
- The Statistical Analysis of Functional MRI Data
- Visual Cortex and Deep Networks: Learning Invariant Representations
- MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
- nilearn: machine learning for neuroimaging in Python
- visbrain: brain data visualization in Python
- PREPARE: Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge - DrivenData - 2023.
- Ultrasound Nerve Segmentation: identify nerve structures in ultrasound images of the neck - Kaggle - 2016
- Melbourne University AES/MathWorks/NIH Seizure Prediction: predict seizures in long-term human intracranial EEG recordings - Kaggle - 2016
- Grasp-and-Lift EEG Detection: identify hand motions from EEG recordings - Kaggle - 2015
- CONNECTOMICS: reconstruct the wiring between neurons from fluorescence imaging of neural activity - Kaggle - 2014
- DecMeg2014 - Decoding the Human Brain: predict visual stimuli from MEG recordings of human brain activity - Kaggle - 2014
- UPenn and Mayo Clinic's Seizure Detection Challenge: detect seizures in intracranial EEG recordings - Kaggle - 2014
- American Epilepsy Society Seizure Prediction Challenge: predict seizures in intracranial EEG recordings - Kaggle - 2014
- Predicting Parkinson's Disease Progression with Smartphone Data - Kaggle - 2013
- Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach - 2019
- Improved Grading of Prostate Cancer Using Deep Learning - 2018
- Histopathologic Cancer Detection: identify metastatic tissue in histopathologic scans of lymph node sections - Kaggle - 2019
- Data Science Bowl 2017: Can you improve lung cancer detection? - Kaggle - 2017
- Intel & MobileODT Cervical Cancer Screening: which cancer treatment will be most effective? - Kaggle - 2017
- Personalized Medicine: redefining cancer treatment - Kaggle - 2017
- Deep Learning for Detection of Diabetic Eye Disease - Google - 2016.
- Diabetic Retinopathy Detection: identify signs of diabetic retinopathy in eye images - Kaggle - 2015
- Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologist - 2017
- SpineNet: Automated classification and evidence visualization in spinal MRIs - 2017
- MURA: Bone X-Ray Deep Learning Competition - Stanford ML Group - open
- Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19 - 2020
- Meta-Learning Initializations for Low-Resource Drug Discovery - 2020
- Merck Molecular Activity Challenge: help develop safe and effective medicines by predicting molecular activity - Kaggle - 2012
- Predicting a Biological Response: predict a biological response of molecules from their chemical properties - Kaggle - 2012
- Feeling Anxious? Perceiving Anxiety in Tweets using Machine Learning - 2019
- A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD) - 2019
- MLSP 2014 Schizophrenia Classification Challenge: diagnose schizophrenia using multimodal features from MRI scans - Kaggle - 2014
- Psychopathy Prediction Based on Twitter Usage - Kaggle - 2012