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Project Amber’s team have developed technology that combines MLand AI techniques with EEG to brain wave to diagnose depression.
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How is data science helping with the COVID-19 pandemic? Modeling relationships to accelerate understanding of disease dynamics
Machine Learning in healthcare can be applied to digitally prognose (predictive diagnosis) using the risk factors of a disease. ML can detect patterns of certain diseases with patient electronic health records and report anomalies to the pattern. ML Diagnostic applications are increasingly being used to supplement clinicians’ decisions, using data lakes to condensify millions of observations of diseases. To instantiate the power of machine learning as a medical prognostic tool, I examined its use in cervical cancer to classify one’s risk of having it, using risk factors, using a publicly available Cervical Cancer Risk Classification Data Set. In this tutorial, you'll see Using Machine Learning to Prognose Cervical Cancer: A Step by Step Guide
Health care has come a long way and with the integration of artificial intelligence, ML and NLP, clinicians can derive insights from data faster.
Improve Glaucoma Assessment with Brain-Computer Interface and Machine Learning. My research used multitask learning to provide rapid point-of-care diagnostics to detect peripheral vision loss
In this article, we shall identify melanoma from the patient’s diagnosis records and images of their skin lesion by applying several machine learning algorithms to classify the lesion as benign or malignant.
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New Diabetes Management Tech Finally Moves Beyond the Bells and Whistles. Users may welcome the update to personalize automated insulin dosing, but they still await a cure.
How AI Voice Assistants Can Revolutionize Health. Siri, Alexa, Google and the future of voice and health technology
‘Sherlock Holmes’ AI Diagnoses Disease Better Than Your Doctor, Study Finds. Peer-reviewed study says you’ll soon consult Dr. Bot for a second opinion