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Artificial Intelligence: Improving Clinical Diagnoses and Patient Outcomes
It is unfortunate, but medical diagnostic errors are actually quite common. As many as 12 to 18 million medical diagnostic errors occur every year in the US. That’s about 5 percent of all clinal diagnostic tests. This is a contributor to the third leading cause of death in the US: medical errors.
Medical diagnostic error numbers though are likely to improve as AI and machine learning algorithms are increasingly applied to clinical diagnoses. Recent studies have shown that machine learning algorithms trained on massive amounts of historical clinical test data can make more accurate clinical diagnoses than humans.
Marc Lanovaz, researcher at the Université de Montréal, compared diagnoses of humans with machine learning results. “The five professionals only came to the same conclusions approximately 75 percent of the time. More importantly, machine learning produced fewer decision-making errors than did all the professionals.”
Despite the potential of using AI in helping with diagnoses, doctors are reluctant to accept machine learning recommendations.
Paul Cerrato, researcher at the Mayo clinic, said that “if you look under the hood so to speak, and you look at these mind bending mathematical equations and the advanced statistics that are needed to create these neural networks and random forest analyses, they really are beyond comprehension of the average physician. So what often happens is they say, ‘I don’t believe it. I can’t say that it’s true.’ But what they’re often really saying is they don’t understand it. Targeted education can help docs understand these complicated algorithms in relatively plain English.”
Ultimately, adoption of AI will free up time for doctors to spend with patients. Currently US physicians average 13 to 16 minutes during an office visit. Michael Rosenberg, CEO of MaxQ, said that “as AI reduces the routine parts of the clinician’s work and expedites the time needed amid diagnosis and treatment, clinicians can spend every precious minute available with their patients – accentuating the human touch that is invaluable for effective and sensitive patient care.”
