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There are additional use cases for leveraging continuous video observation beyond monitoring patients for fall risk. And AI has a role to play. Caregility's chief strategy officer explains.
(Sponsored) Artificial intelligence and machine learning can be used to unleash the true potential of data and help to address the health equity gaps, while improving the patient experience, says Andrew Miles, EMEA Head Healthcare at Google Cloud.
Bias in dermatology toward white skin can result in missed diagnoses for people of color, say VisualDx physicians.
Professor Karol Sikora, chief medical officer at Rutherford Health, highlights the most pressing needs in cancer treatment today and how he envisages treatment decision-making in the next decade.
The future of AI includes a vision for a keyboard free environment, bringing joy back to the medical profession.
Brian Robertson, CEO of VisiQuate, describes how new machine learning tools are helping surface relevant information where and when it's needed, and discusses broader trends in AI and automation across the healthcare space.
Providers need prescriptive analytics to lower their risk in value-based contracts, says Sheila Talton, CEO of Gray Matter Analytics.
DrFirst President Cameron Deemer explains how practical machine learning applications can help improve safety and efficiency – automating medication history in hospital EHRs and aggregating patient records in consumer apps.
Remote monitoring technology can expand the reach of clinical trials, says Jennifer Price, executive director of data and analytics at THREAD.
Jonathan Weiner, professor at Johns Hopkins Bloomberg School of Public Health, discusses some of the data fundamentals necessary for effective AI and machine learning algorithms.