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Honggang Yu
Medical School
Wuhan University
Hubei
Language: English, Chinese, German
Gastrointestinal
Tumors
Early Diagnosis
Treatment
Artificial Intelligence
Endoscopy
Research
Molecular Mechanisms
Metastasis
Chemoresistance
Areas of Focus
- Early diagnosis and treatment of gastrointestinal tumors
- Artificial intelligence research in digestive endoscopy
- Molecular mechanisms of invasion, metastasis, and chemoresistance in gastrointestinal tumors
Work Experience
- 1991.07 - 1993.07 Resident Doctor, Hubei Provincial People's Hospital (now Renmin Hospital of Wuhan University)
- 1996.07 - 1998.01 Attending Physician, Hubei Provincial People's Hospital (now Renmin Hospital of Wuhan University)
- 2002.04 - 2005.07 Professor, Master's Supervisor, Department of Gastroenterology, Renmin Hospital of Wuhan University
- 2005.07 - Present Professor, Doctoral Supervisor, Department of Gastroenterology, Renmin Hospital of Wuhan University
- 2007.12 - Present Director of Gastroenterology, Renmin Hospital of Wuhan University
Academic Background & Achievements
- 1986.09 - 1991.02 Bachelor's Degree: Tongji Medical University
- 1993.09 - 1996.07 Master's Degree: Hubei Medical University (now Wuhan University Medical Department)
- 1998.04 - 2000.07 PhD: University of Düsseldorf, Germany
- 2000.03 - 2002.04 Postdoctoral Research: Molecular Digestive Laboratory, St.-Josef-Hospital, Bochum University, Germany
- 2006.10 - 2007.06 Postdoctoral Research Fellow: Scripps Research Institute, USA
- 2007.07 - 2007.11 Postdoctoral Research: University of California, San Diego, USA
Publications
- Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study, Zhou W, Yao L, Wu H, et al., 2021
- Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy, Wu L, Zhang J, Zhou W, et al., 2019
- Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial, Wu L, Shang R, Sharma P, et al., 2021
- Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study, Gong D, Wu L, Zhang J, et al., 2020
- A deep neural network improves endoscopic detection of early gastric cancer without blind spots, Wu L, Zhou W, Wan X, et al., 2019
- A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy, Ling T, Wu L, Fu Y, et al., 2021
- Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: a randomized controlled trial, Wu L, He X, Liu M, et al., 2021
- Intelligent difficulty scoring and assistance system for endoscopic extraction of common bile duct stones based on deep learning: multicenter study, Huang L, Lu X, Huang X, et al., 2021
- An artificial intelligence-based quality improvement system significantly improved the efficacy of computer-aided detection system in colonoscopy: A four group parallel study, Yao L, Zhang L, Liu J, et al., 2021
- Comparing blind spots of unsedated ultrafine, sedated, and unsedated conventional gastroscopy with and without artificial intelligence: a prospective, single-blind, 3-parallel-group, randomized, single-center trial, Chen D, Wu L, Li Y, et al., 2020
- A novel artificial intelligence system for the assessment of bowel preparation (with video), Zhou J, Wu L, Wan X, et al., 2020
- Deep learning-based pancreas segmentation and station recognition system in EUS: development and validation of a useful training tool (with video), Zhang J, Zhu L, Yao L, et al., 2020
- Automated and real-time validation of gastroesophageal varices under esophagogastroduodenoscopy using a deep convolutional neural network: a multicenter retrospective study (with video), Chen M, Wang J, Xiao Y, et al., 2021
- Artificial intelligence in the diagnosis of gastric precancerous conditions by image-enhanced endoscopy: a multicenter, diagnostic study (with video), Xu M, Zhou W, Wu L, et al., 2021
- Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos), Wu L, Wang J, He X, et al., 2022
- Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos), Wu L, Xu M, Jiang X, et al., 2021
- Real-time use of artificial intelligence for diagnosing early gastric cancer by magnifying image-enhanced endoscopy: a multicenter, diagnostic study (with videos), He X, Wu L, Dong Z, et al., 2021
- Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video), Lu Z, Xu Y, Yao L, et al., 2021
- A deep learning method for delineating early gastric cancer resection margin under chromoendoscopy and white light endoscopy, An P, Yang D, Wang J, et al., 2020
- A deep learning-based system for bile duct annotation and station recognition in linear endoscopic ultrasound, Yao L, Zhang J, Liu J, et al., 2021
- A Novel Model Based on Deep Convolutional Neural Network Improves Diagnostic Accuracy of Intramucosal Gastric Cancer (With Video), Tang D, Zhou J, Wang L, et al., 2021
- Impact of Computer-Assisted System on the Learning Curve and Quality in Esophagogastroduodenoscopy: Randomized Controlled Trial, Huang L, Liu J, Wu L, et al., 2021
- Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography, Chen J, Wu L, Zhang J, et al., 2020
- A Gastrointestinal Endoscopy Quality Control System Incorporated With Deep Learning Improved Endoscopist Performance in a Pretest and Post-Test Trial, Yao L, Liu J, Wu L, et al., 2021
- Artificial intelligence in upper GI endoscopy - current status, challenges and future promise, Yu H, Singh R, Shin SH, Ho KY, 2021
- A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video), Chen D, Yu Y, Zhou Y, et al., 2021
- Expert-level classification of gastritis by endoscopy using deep learning: a multicenter diagnostic trial, Mu G, Zhu Y, Niu Z, et al., 2021
- A deep learning-based system for real-time image reporting during esophagogastroduodenoscopy: a multi-center study, Unknown
Awards
- 2021: First Prize, Technological Invention Award of Hubei Province
- 2017: Second Prize, Scientific and Technological Progress Award of Hubei Province
- 2005: Third Prize, Natural Science Award of Hubei Province
