Should AI assist in surgical decision-making?


INTRO: The first and second leading causes of death in the United States are heart disease and cancer. The third is now coronavirus. Know what's next? Astoundingly, the answer is preventable medical errors.

Surgical errors in particular account for 26% of these deaths and cost somewhere north of $36 billion in the U.S. I did a double take when I read those stats while reporting this story. Some of the most common laparoscopic procedures, things like colectomies, hysterectomies, and gastrectomies result in an astounding number of preventable deaths.

Fully automated surgeries performed by robots is still a ways off. In the meantime, developers are trying to beat those grim numbers by harnessing the best of human decision making and coupling it with truly exceptional technology tools designed to assist surgeons. Artificial intelligence and machine learning are often touted as solutions for call centers and to provide intelligent insights to companies that have reams of data that needs to be processed, but leveraging AI/ML to better medical outcomes could be one of the transformative technologies of our time.

"Surgical decision-making is dominated by hypothetical-deductive reasoning, individual judgment, and heuristics," write the authors of a recent JAMA Surgery paper called Artificial Intelligence and Surgical Decision-making. "These factors can lead to bias, error, and preventable harm. Traditional predictive analytics and clinical decision-support systems are intended to augment surgical decision-making, but their clinical utility is compromised by time-consuming manual data management and suboptimal accuracy."

The paper's authors propose AI as an effective augmentation tool to enhance in situ surgical decision making. We're already seeing the first examples of this come to market... (MORE)

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