General Overview of Artificial Intelligence for Interstitial Cystitis in Urology
- Affiliations
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- 1Department of AI Center, Korea University Anam Hospital, Seoul, Korea
- 2Department of Urology, Chungnam National University Sejong Hospital, Chungnam National University College of Medicine, Sejong, Korea
- 3GRK Partners Research Center, Seoul, Korea
Abstract
- Our understanding of interstitial cystitis/bladder pain syndrome (IC/BPS) has evolved over time. The diagnosis of IC/BPS is primarily based on symptoms such as urgency, frequency, and bladder or pelvic pain. While the exact causes of IC/BPS remain unclear, it is thought to involve several factors, including abnormalities in the bladder’s urothelium, mast cell degranulation within the bladder, inflammation of the bladder, and altered innervation of the bladder. Treatment options include patient education, dietary and lifestyle modifications, medications, intravesical therapy, and surgical interventions. This review article provides insights into IC/BPS, including aspects of treatment, prognosis prediction, and emerging therapeutic options. Additionally, it explores the application of deep learning for diagnosing major diseases associated with IC/BPS.