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Journal of Medical Signals and Sensors، جلد ۱۵، شماره ۲، صفحات ۱۰-۴۱۰۳
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Isfahan Artificial Intelligence Event 2023: Reflux Detection Competition
چکیده انگلیسی مقاله Abstract Background:  Gastroesophageal reflux disease (GERD) is a prevalent digestive disorder that impacts millions of individuals globally. Multichannel intraluminal impedance-pH (MII-pH) monitoring represents a novel technique and currently stands as the gold standard for diagnosing GERD. Accurately characterizing reflux events from MII data are crucial for GERD diagnosis. Despite the initial introduction of clinical literature toward software advancements several years ago, the reliable extraction of reflux events from MII data continues to pose a significant challenge. Achieving success necessitates the seamless collaboration of two key components: a reflux definition criteria protocol established by gastrointestinal experts and a comprehensive analysis of MII data for reflux detection. Method:  In an endeavor to address this challenge, our team assembled a dataset comprising 201 MII episodes. We meticulously crafted precise reflux episode definition criteria, establishing the gold standard and labels for MII data. Result:  A variety of signal-analyzing methods should be explored. The first Isfahan Artificial Intelligence Competition in 2023 featured formal assessments of alternative methodologies across six distinct domains, including MII data evaluations. Discussion:  This article outlines the datasets provided to participants and offers an overview of the competition results.
کلیدواژه‌های انگلیسی مقاله 24-h monitoring,deep learning,Isfahan Artificial Intelligence Challenge,multichannel intraluminal impedance,reflux
نویسندگان مقاله | Azra Rasouli Kenari
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Ahmadreza Montazerolghaem
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Zahra Zojaji
Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran


| Mehdi Ghatee
Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran


| Behnam Yousefimehr
Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran


| Amin Rahmani
Regenerative Medicine Research Center, Isfahan University of Medical Science, Isfahan, Iran


| Mahdi Kalani
4.Regenerative Medicine Research Center, Isfahan University of Medical Science, Isfahan, Iran 5.Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran


| Farnoush Kiyanpour
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Mohamad Kiani-Abari
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Mohammad Yasin Fakhar
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Safiyeh Rezaei
Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran


| Mojtaba Tahernia
Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran


| Mohammad Hossein Vafaie
Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran


| Hamidreza Besharatnezhad
School of Electrical engineering, Iran University of Science and Technology, Tehran, Iran


| Vahid Rahimi Bafrani
Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran


| Mohamad Taghi Tofighi


| Peyman Adibi Sedeh
Isfahan Gastroenterology and Hepatology Research Center, Department of Internal Medicine, Isfahan University of Medical Sciences, Isfahan, Iran


| Maryam Soheilipour
Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran


| Hossein Rabbani


نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/743
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Methodology Articles
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