Colorectal polyp prevalence and adenoma detection rates in an Iranian cohort: a prospective study by Amir-Hossein Mousavian, Anahita Sadeghi, Amir Kasaeian, Maryam Rayatpisheh, Sepideh Nikfam, Marziyeh Malek, Reza Malekzadeh, Siavosh Nasseri-Moghaddam

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Panoramic colonoscopy in colorectal cancer screening – a randomized controlled trial by Paweł Bogacki, Tomasz Gach, Jan Krzak, Mirosław Szura

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MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with Application in Colonic Polyp Image Segmentation by Chen Peng, Zhiqin Qian, Kunyu Wang, Lanzhu Zhang, Qi Luo, Zhuming Bi, Wenjun Zhang

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Increased quality of bowel preparation via smartphone WeChat application: a multicenter randomized controlled trial by Jing Wen, Jia Feng, Cuihua Liu, Dianhui Yang, Yangyang Zhang, Nali Lu, Jianmei Yu, Yanxin Gao, Ruli Sheng, Jianhua Wang, Jin Huang

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Introducing a Deep Neural Network Model with Practical Implementation for Polyp Detection in Colonoscopy Videos by Hajar Keshavarz, Zohreh Ansari, Hossein Abootalebian, Babak Sabet, Mohammadreza Momenzadeh

Subjects: “…automatic polyp detection…”
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A comparative study benchmarking colon polyp with computer‐aided detection (CADe) software by Nikolaos Papachrysos, Pia Helén Smedsrud, Kim V. Ånonsen, Tor Jan D. Berstad, Håvard Espeland, Andreas Petlund, Per J. Hedenström, Pål Halvorsen, Jonas Varkey, Hugo L. Hammer, Michael A. Riegler, Thomas deLange

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Insights from age-stratified endoscopic detection metrics support initiating colorectal cancer screening at age 45 by Majd Khader, Jorge-Shmuel Delgado, Rimon Artoul, Asher Shafrir, Abu-Freha Naim

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Editorial: Artificial intelligence for early diagnosis of colorectal cancer by Luisa F. Sánchez-Peralta, Benjamin Glover, Debesh Jha, J. Blas Pagador

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Real-Time Polyp Detection From Endoscopic Images Using YOLOv8 With YOLO-Score Metrics for Enhanced Suitability Assessment by Zahid Farooq Khan, Muhammad Ramzan, Mudassar Raza, Muhammad Attique Khan, Areej Alasiry, Mehrez Marzougui, Jungpil Shin

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A complete benchmark for polyp detection, segmentation and classification in colonoscopy images by Yael Tudela, Mireia Majó, Neil de la Fuente, Adrian Galdran, Adrian Krenzer, Frank Puppe, Amine Yamlahi, Thuy Nuong Tran, Bogdan J. Matuszewski, Kerr Fitzgerald, Cheng Bian, Junwen Pan, Shijle Liu, Gloria Fernández-Esparrach, Aymeric Histace, Jorge Bernal

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Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation by Ojonugwa Oluwafemi Ejiga Peter, Opeyemi Taiwo Adeniran, Adetokunbo MacGregor John-Otumu, Fahmi Khalifa, Md Mahmudur Rahman

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Real-Time Artificial Intelligence-Assisted Colonoscopy and the Effect of Endoscopist Experience on Polyp Detection Rates at a Tertiary Referral Center by Isaac Seow-En

Subjects: “…adenoma detection rate; artificial intelligence-assisted colonoscopy; computer-aided detection; gi genius; polyp detection rate…”
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Exploring intraprocedural performance in colonoscopy: Insights from a tertiary care center in Saudi Arabia by Abdulla I. Yateem, Abdulrahman M. Saleh, Dimah A. Alaskar, Ali S. AlGarni, Anwar B. Alotaibi, Fuad Y. Maufa, Abdelhaleem Bella

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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

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