Abstracts being presented at the American Urological Association's Annual Meeting discuss an AI chatbot created by urologists that provides accurate urologic information to patients and a series of algorithms developed to accurately predict a urine culture's sensitivity to antibiotics up to three days prior to culture results.
Researchers will present their study findings covering important updates on technology in San Antonio, Texas, from May 3 to 6. Jacob Taylor, MD, urologic oncology fellow at UT Southwestern Medical Center, moderated a virtual press session with the abstract authors, providing key insights into their research.
“This is all very exciting data and new technology that is already here and being used with patients,” said Dr. Taylor. “I think these studies will improve patient care for a wide range of the most common urologic conditions.”
The following abstracts are covered in the moderated panel:
- Machine Learning Models Employed At The Time Of Urine Specimen Collection Predict Antibiotic Resistance On Final Culture
- Effectiveness Of The Medical Chatbot PROSCA To Inform Patients About Prostate Cancer: Results Of A Randomized Controlled Trial
- Can We Predict IPSS Scores With Voiding Performance On Home-Based Uroflowmetry Data Using A Smartphone Application?
A recording of the panel discussion is available to all press registrants. Fill out the registration form on the website to be added to the virtual programming: https://www.auanet.org/AUA2024/register/press-registration
Source: https://www.auanet.org/