The Role of Artificial Intelligence in Kidney Calculi Management: A Systematic Review

سال انتشار: 1404
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 19

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شناسه ملی سند علمی:

AIMS02_294

تاریخ نمایه سازی: 29 تیر 1404

چکیده مقاله:

Background and Aims: Kidney Stone are one of the most common urinary tract diseases, with a prevalence of ۱-۱۵% in all age groups. Recently, AI has presented innovative solutions in the management of kidney Stone, but the evidence is sparse. So, this systematic review was conducted to analyze the impact of AI in areas such as diagnosis, treatment, and prevention of kidney Stone. Methods: In this systematic review, extensive searches were performed with keywords related to 'artificial intelligence' and 'kidney Calculi' in the international databases of Web of Science Core Collection, PubMed/Medline Scopus, Google_Scholar search engine, and national databases of Irandoc, SID, and Magiran. The initial search yielded ۳۹ studies. Inclusion criteria were publication in Persian/English. Grey literature came out. The time limit wasn't applied. After eliminating duplicates and critiquing with relevant tools, at least seven studies were analyzed. Ethical considerations of non-bias were observed at the stages of selection, extraction, analysis, and classification of evidence, and the abstract was reported according to PRISMA. Results: Studies have shown that using AI algorithms can increase the accuracy of detection of kidney Stone composition to more than ۹۰% and improve the accuracy of Fourier transform infrared spectroscopy(FTIR) analyses to detect laboratory errors in determining Calculi composition. A transferential learning model using VGG۱۶ with Explainable AI(XAI) helps doctors accurately diagnose kidney Stone. ChatGPT is also useful in urological diagnoses but requires professional supervision. Also, using a Decision Support System(DSS) with ۹۴.۸% accuracy is effective in predicting the results of a specific treatment for kidney Stone. The UroGPT AI bot can also assist patients with kidney Stone in accessing information and managing self-care. When comparing chatbots' accuracy in categorizing foods based on oxalate content, Bard AI performed best with ۸۴% accuracy, followed by GPT-۴, Bing Chat, and GPT-۳.۵. Conclusion: It seems that the use of AI can help urologists provide advice, choose the type of treatment, and

نویسندگان

Zahra Abdollahi

Master’s student, Department of Medical Surgical Nursing, Student Research Committee, School of Nursing and Midwifery, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Narges Mohamadi

Master’s degree student in Medical surgical nursing, Faculty of Medical Sciences, Yazd Branch, Islamic Azad University, Yazd, Iran

Hossein Zamani

Master’s student in Medical Surgical nursing, Student Research Committee, Yasuj University Of Medical Science, Yasuj, Iran