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KMID : 1240020230270000064
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International Neurourology Journal
2023 Volume.27 No. 0 p.64 ~ p.72
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General Overview of Artificial Intelligence for Interstitial Cystitis in Urology
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Cho Yong-Won
Park Jong-Mok
Youn Seung-Hyun
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Abstract
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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.
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KEYWORD
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Interstitial cystitis, Diagnosis, Treatment, Convolutional neural network, Deep learning, Large language model
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