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@researchbavaria 2 years ago
New #Supramolecular materials can be used in #EnergyProduction & #MedicalDevices. A team at the @TU_Muenchen Innovation Network #ARTEMIS aims to identify the best materials for use with the help of #MachineLearninghttps://www.research-in-bavaria.de/supramolecular-materials #PlsRT @MedBioinorgChem
@DalithSteiger 4 years ago
Israeli start-up aims to marry #MachineLearning with medicine. But instead of raising hundreds of millions of dollars from high-profile investors, the company only wants to be paid if enough patients take its tests. https://bit.ly/3bALxDV #CongnitiveNews
@SwissCognitive 4 years ago
Israeli start-up aims to marry #MachineLearning with medicine. But instead of raising hundreds of millions of dollars from high-profile investors, the company only wants to be paid if enough patients take its tests. https://bit.ly/3bALxDV #CongnitiveNews
@SwissCognitive 4 years ago
A new @Cornell research aims to coalesce #MachineLearning & #Medicine, with the goal of improving methods for disease detection and diagnosis. http://ow.ly/wOXV30qePLX @cornell_tech @WeillCornell @IUPedu @C3NL_ICL #ML #AI #CognitiveNews
@daniel_kraft 4 years ago
An interactive data-science system called Northstar from @MIT & @BrownUniversity aims to democratize data science by making it easy for nonspecialists to use machine-learning models to make predictions for medicine & beyond http://news.mit.edu/2019/drag-drop-data-analytics-0627 #AI #ML #BigData h/t @ZGJR
@AcadayLabs 6 years ago
New Era, new Ethics : Proof Work aims to decentralize #Medical data by using the blockchain http://goo.gl/alerts/YZqtL #DataScience #AI #ML #DL #InternetOfThings #ArtificialIntelligence #MachineLearning #DeepLearning #BlockChain #Technology #data #Blockchain #MEDTECH #MedtechRising
@WIRED 6 years ago
Qualcomm is developing an entirely new kind of healthcare—one where tools like VR help doctors better understand, diagnose, and treat patients in real life.
@WIRED 9 years ago
The problem Apple's ResearchKit hopes to solve is the difficulty in getting big data about disease.