Machine learning can predict adverse outcomes following abdominal hernia surgery скачать в хорошем качестве

Machine learning can predict adverse outcomes following abdominal hernia surgery

Researchers from University of Texas MD Anderson Cancer Center (Houston) have developed new machine learning models that can predict the risk of hernia recurrence and other complications after abdominal hernia repair with an accuracy of up to 85%. These models can also identify factors associated with poor outcomes for shared decision making between patients and surgeons to encourage changes in patient behaviors before surgery to improve success in abdominal wall reconstruction operations. Published in the Journal of the American College of Surgeons. About American College of Surgeons: The American College of Surgeons (ACS) is a scientific and educational association of surgeons that was founded in 1913 to improve the quality of care for the surgical patient by setting high standards for surgical education and practice and is headquartered in Chicago, IL. The College is a surgical society dedicated to promoting the highest standards of surgical care through education of, and advocacy for, its Fellows and their patients, and to safeguarding standards of care in an optimal and ethical practice environment. Get more ACS: YouTube:    / amcollegeofsurgeons   Twitter:   / amcollsurgeons   Facebook:   / amcollsurgeons   Instagram:   / amcollsurgeons