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@calvin_zcx 1 year ago
Super glad to give a lecture @cornell_tech on using #MachineLearning and #EHR #RWD data to understand #LongCovid, covering our latest Nature Communication and Nature Medicine papers https://t.co/6K9CsXPBal
@HubXChange1 4 years ago
#HealthIT #MachineLearning - #ML Mixed Pooling Multi-View Attention #Autoencoder for Representation Learning in #Healthcare #Data: Electronic #Health / #Medical Records - #EHR / #EMR ️https://arxiv.org/abs/1910.06456 @HubBucket @HubXChange1 @HubBaseDB @HubAnalytics1 @HubAnalysis1 https://t.co/5tRUamIdbA
@HubXChange1 4 years ago
#HealthIT #MachineLearning Semi-Supervised Natural Language Processing - #NLP/#NLProc Approach for Fine-Grained Classification of Electronic #Medical Records - #EMR and Electronic #Health Records - #EHR Reports ️https://arxiv.org/abs/1910.13573 @HubBucket @HubXChange1 @HubBaseDB https://t.co/BTQk62FVNM
@alvie_barr 4 years ago
Interesting read The medical #ArtificialIntelligence insurgency: what physicians must know about #data to practice with intelligent machines (Read highlighted) Link: https://www.nature.com/articles/s41746-019-0138-5 #AI #MedTwitterAI #MedTwitter #ML #MachineLearning #DataScience #BigData #EMR #EHR https://t.co/RKr8BS8inl
@KirkDBorne 6 years ago
Google is Using 46 Billion Data Points to Predict the Medical Outcomes of Hospital Patients: https://qz.com/1189730/google-is-using-46-billion-data-points-to-predict-the-medical-outcomes-of-hospital-patients/ #Healthcare #BigData #DataScience #AI #MachineLearning #DeepLearning #DataMining #HealthTech #EHR https://t.co/85UYuXlPI3
@FrRonconi 6 years ago
#Google is using 46 billion #data points to predict the #medical outcomes of hospital patients https://qz.com/1189730 via @qz #AI #MachineLearning #HealthTech #DigitalHealth #EHR #BigData #PatientEngagement HT @evankirstel @JohnNosta https://t.co/tEcRykikbo