Tag: Clinical Trial

6 Ways - How #AI Can Help in the #Healthcare Industry

6 Ways – How #AI Can Help in the #Healthcare Industry

EMed HealthTech

AI is rapidly #revolutionising the #healthcare #industry #worldwide – continuously learning and adapting.- Identifying the potential impact of a drug- Helps in making better-informed decisions- Helps in the early #diagnosis of a #disease- Improves other #technologies like #AR and #VR also- It helps in the #research and discovery of #medicines- It helps in #identifying the right candidates for #clinical trialsView more about #digital #transformation #trends at: https://www.emedhealthtech.com/6-healthcare-digital-transformation-trends-2022/#digitalhealth #healthsoftware #healthapp #Blockchain #ml #rpa #healthcareit #telehealth…

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New York approves AI-driven breast cancer diagnostic

New York approves AI-driven breast cancer diagnostic

Healthcare IT news

With Clinical Laboratory Evaluation Program assay validation, the company’s Clinical Laboratory Improvement Amendments-certified lab can begin testing patient samples.WHY IT MATTERS
Along with New York State Department of Health clinical and analytical validation of this use of array morphology, the results of the PDxBr test were reproducible.
“Consistent with our mission of improving healthcare, PDxBr has shown to be an effective prognostic tool to further improve risk stratification over current histopathology methods,” said Wayne Brinster, CEO of PreciseDx, in an announcement.
The company says the AI technology has now proven its ability to enhance invasive breast cancer pathology interpretation with objective, quantifiable and accurate…

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Johns Hopkins AI models predict ICU delirium risk

Johns Hopkins AI models predict ICU delirium risk

Healthcare IT news

Two dynamic analytics models developed at Johns Hopkins University predicted delirium-prone patients when tested on two datasets drawn from 100,000 stays at a Boston hospital’s intensive care unit, according to new research.WHY IT MATTERS
Delirium – sudden bouts of confusion, inattention, paranoia, agitation and hallucinations – can put patients at higher risk of prolonged hospitalization, future dementia and death. By forecasting delirium, alerted clinicians could apply countermeasures that can mitigate adverse outcomes, according to the premise of artificial intelligence research published in Anesthesiology. 
“For a lot of these physiological transitions, we think that there are early warning signs that may not be obvious…

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