Data science is helping to expand knowledge in healthcare and to predict outcomes of medical treatments.
“Predictive models,” as they are known, use speech, behavior, and social media patterns as well as machine learning and algorithms to analyze data and develop future expectations.
The more practice and the more data, the more accurate the predictive models should become. They could enable doctors to more astutely predict your likelihood to contract a specific illness or prescribe a more successful treatment.
Speech
One recent big breakthrough was engineered by researchers at Boston University.
They say they have created an artificial intelligence computer program built to analyze a patient’s speech.
“Their model can predict, with an accuracy rate of 78.5 percent, whether someone with mild cognitive impairment is likely to remain stable over the next six years—or fall into the dementia associated with Alzheimer’s disease,” according to a report at foreseemed.com.
“While allowing clinicians to peer into the future and make earlier diagnoses, the researchers say their work could also help make cognitive impairment screening more accessible by automating parts of the process—no expensive lab tests, imaging exams, or even office visits required.”
Prevent no-shows
Predictive modeling also can shape patient behavior.
A Duke University study said predictive modeling could identify patients likely to skip appointments and then offer them reminders and other encouragement to see their physicians.
Learn more about predictive modeling at pmc.ncbi.nlm.nih.gov/articles/PMC10637620/.
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