Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and #MachineLearning algorithms @LHCHFT @LJMU_Health @LivHPartners @LivuniILCaMS https://link.springer.com/article/10.1007/s11739-023-03297-6 https://t.co/EF1kSYN78v
Doctomatic is a remote patient-monitoring app which, using any medical device from heart-rate monitors to scales, allows doctors to check in on patients with chronic disease. :Gregori Civera https://wired.trib.al/80BpwK6 5/12 https://t.co/PLl8Etgl2V
#Python can turn you into a medical doctor So I spent the day analysing data of 70000 patients from a hospital using python and jupyter notebook. Cholesterol and Weight are the 2 big diff between those with/without cardio disease #100DaysOfCode #Coding #DataScience https://t.co/xL1lW6QYUL
Our paper on Benchmarking AutoML frameworks for disease prediction using medical claims is out in @BioDataMining https://biodatamining.biomedcentral.com/articles/10.1186/s13040-022-00300-2 #automl #bioinformatics #machinelearning
Using the power of #ArtificialIntelligence to detect disease by @ANSTO @medical_xpress Read more https://bit.ly/3vhQIDj #AI #HealthTech #MedTech #DeepLearning #DataScience #Innovation Cc: @grattonboy @amuellerml https://t.co/kucFNcFWXd
Our new preprint is out! Decentralized and privacy-protecting disease prediction using #swarmlearning, the way forward for collaborative precision medicine. Awesome collaboration with @HPE! #COVID19 #machinelearning #blockchain https://www.biorxiv.org/content/10.1101/2020.06.25.171009v1
Johns Hopkins Medicine is tapping vast amounts of data to better predict disease progression using #Cloud and #MachineLearning: http://msft.social/lPanHu #AI @HopkinsMedicine https://t.co/OO8A0aZlxE