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How Machine Learning Can Connect Patients and Physicians

Samara Rosenfeld
APRIL 30, 2019


Machine learning and artificial intelligence (AI) have proven to be beneficial for physicians and specialists to improve outcomes during surgeries and aid in the efficient diagnosis of certain diseases and conditions.

While the technologies have highlighted efficiencies in the doctor and hospital settings, they have also been used in digital health applications and even to help match patients with physicians.

Suzanne Clough, M.D., chief innovation officer at ArmadaHealth, a health data sciences and services company, told Inside Digital Health™ at World Healthcare Congress 2019 that machine learning helps to better understand the different types of interactions between physicians and patients.

Clough likes to think of what ArmadaHealth is doing as the “e-Harmony” for patient-physician matching.

And with modalities like machine learning, ArmadaHealth can learn more in depth about what the patient is looking for in a physician — what makes the patient tick and what beyond the obvious clinical match can be gleaned to make the match a meaningful experience for the patient and physician.

Machine learning can help companies and health systems alike to test hypotheses and leverage all of the collected data to drive better clinical insights and outcomes.

“So, when you think about all the complexities that go into what can actually drive good clinical outcomes, some of that is just beyond human computing,” Clough said.

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