MIT CSAIL researchers claim their algorithm helps doctors pick the right antibiotics

Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) say they've developed a recommendation algorithm that predicts the probability a patient's urinary tract infection (UTI) can be treated by first- or second-line antibiotics. With this information, the model makes a recommendation for a specific treatment that selects a first-line agent as frequently as possible, without leading to an excess of treatment failures. UTIs, which affect half of all women, add almost $4 billion a year in health care costs. Doctors often treat UTIs using antibiotics called fluoroquinolones, but they've been found to put women at risk of contracting other infections. They're also associated with a higher risk of tendon injuries and life-threatening conditions like aortic tears, leading medical associations to issue guidelines recommending fluoroquinolones as "second-line treatments."