Medical Technology

@youldash 1 year ago

After a work that lasted many months with considerable setbacks, I've finally completed the AI for Healthcare #Udacity Nanodegree program. Highly recommended to those interested in applying #MachineLearning, #DeepLearning and #DataScience techniques to solving medical challenges. https://t.co/303Oi07cFO

@filip4science 2 years ago

We did a mini-reivew on the impact of #AI on compound discovery, design, and synthesis - all highly relevant medicinal chemistry topics! It’s #openaccess, so give it a read! https://pubs.acs.org/doi/10.1021/acsomega.1c05512 #MachineLearning #chemoinformatics @ACS_Omega #ArtificialIntelligence

@MRAguy 3 years ago

Excellent and highly relevant work by Julia Noothout on fully automatic landmark localization in medical images - this will be very useful clinically. You can find the paper here: https://arxiv.org/pdf/2007.05295.pdf #DeepLearning #MachineLearning @ivanaisgum @BobdeVos @jelmerwolterink https://t.co/RgR2uJxfqM

@GloriusGroup 3 years ago

300 People waiting for the second session on #Molecular #MachineLearning – now we are highly excited to listen to Jürgen Bajorath from @UniBonn, talking about molecular activity prediction from a medicinal chemistry perspective! ⚕️🧪 https://t.co/B71Ngh8a4m

@HumanBrainProj 3 years ago

Prof. Dr. Simon Eickhoff's work focuses on: ◦ Understanding brain organization ◦ #MachineLearning for individual prediction, #clinical translation & personalized #medicine All of which is highly relevant to the mission of the Human Brain Project. Follow him at @INM7_ISN https://t.co/vZe55zoiuU

@INM7_ISN 4 years ago

Eysenk's astonishing work on "cancer personality". If results are too good to be true, there is usually a good reason for this Highly relevant to current work on #MachineLearning in neuroimaging and Medicine. Real life is too complex for >>90% accuracy https://cosmosmagazine.com/society/is-this-one-of-the-worst-scientific-scandals-of-all-time

@raamana_ 5 years ago

Random tip: if a PI publishes over 25 papers/year (more than 2 papers/month), in a heavily data- and optimization-driven research e.g. #MachineLearning in medicine, without releasing their codebase or using public libraries, be HIGHLY skeptical about their results. #phdchat

@KirkDBorne 5 years ago

From highly imbalanced data sets, see how #MachineLearning could be a “game changer” for Medicare Fraud Detection: https://www.hcanews.com/news/how-machine-learning-could-detect-medicare-fraud by @JackMurtha @HCA_News #BigData #DataScience #AI #FraudAnalytics #PredictiveAnalytics #HealthTech +see this book: https://amzn.to/2Uv5C6O https://t.co/zCw5rH6W12

@Atheek_Ahamath 6 years ago

AI powered robots may replace highly trained medical, law and IT professionals by 2022 #machinelearning #bigdata #… http://bit.ly/2pfKRAi