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If it’s to progress from capturing the public’s imagination to earning widespread clinical implementation, healthcare AI has a long road to travel.  

Machine learning is being quickly adapted across the healthcare space to develop precision medicine, and it can also be leveraged to improve the development of new drug treatments and devices by improving the randomized clinical trial process, according to MIT researchers.

A technology company that uses AI to precisely match medical interventions with individual patients has received a $23 million infusion.

Most physicians rightly laugh off talk of their profession’s coming demise at the hands of AI. But more than a few are taking the blossoming technology into account when making career decisions.

Several plant-based foods readily available in supermarkets contain bioactive molecules that could not only prevent cancer but also treat it, accomplishing the latter with protective mechanisms similar to those activated by existing clinical therapies.  

Researchers from Kaiser Permanente have developed a machine learning algorithm that could help prevent the spread of the HIV virus by finding at-risk patients and getting them on prevention medications. The researchers published the findings of their prediction model in The Lancet HIV.

 

From the U.S. by way of the Land Down Under comes a “turbo-charged” flu vaccine created by AI.

It’s not unusual for hospitalized patients to take a sudden turn for the worse. A continuous inspection of electronic medical records by machine-learning algorithms can warn of impending trouble in real time, giving physicians a chance to proactively intervene.

Using a dataset of records from nearly 3 million pediatric patients, South Korean researchers have developed and validated a deep-learning algorithm that can tell emergency doctors which children will need to be admitted to critical-care units.

Hospital inpatients who are likely to turn violent can be identified by algorithmic analysis of routine clinical notes stored in electronic health records, according to a study published in JAMA Network Open July 3.

A graduate-level program that will award certificates on the ethical use of AI across various spheres, including healthcare, is set to launch next month at San Francisco State University.

In a study of machine learning’s ability to predict cardiovascular problems, 10 of 15 models proved more accurate than manual methods of risk assessment.