Techniques to integrate artificial intelligence systems with medical information in gastroenterology
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Bing Hu | Man Zhang | Hong-Yu Jin | Hongyu Jin | Mancong Zhang | Bing Hu
[1] Hype or reality? Will Artificial Intelligence actually make us better at performing optical biopsy of colon polyps? , 2020, Gastroenterology.
[2] Ji Li,et al. Artificial intelligence in inflammatory bowel disease: current status and opportunities , 2020, Chinese medical journal.
[3] J. Sung,et al. Artificial intelligence in gastroenterology: where are we heading? , 2020, Frontiers of Medicine.
[4] K. Ragunath. Artificial intelligence in gastrointestinal endoscopy: how intelligent can it get? , 2019, The Lancet. Oncology.
[5] Andrew Q. Ninh,et al. Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett's esophagus (with video). , 2020, Gastrointestinal endoscopy.
[6] Artificial Intelligence in Endoscopy. , 2019, Gastrointestinal endoscopy.
[7] Hsuan-Ting Chang,et al. Computer-aided diagnosis for identifying and delineating early gastric cancers in magnifying narrow-band imaging. , 2017, Gastrointestinal endoscopy.
[8] S. Menon,et al. How commonly is upper gastrointestinal cancer missed at endoscopy? A meta-analysis , 2014, Endoscopy International Open.
[9] A. Abadir,et al. Artificial Intelligence in Gastrointestinal Endoscopy , 2020, Clinical endoscopy.
[10] Andreas Keller,et al. Deep-learning based detection of gastric precancerous conditions , 2019, Gut.
[11] V. Wong,et al. Machine learning model to predict recurrent ulcer bleeding in patients with history of idiopathic gastroduodenal ulcer bleeding , 2019, Alimentary pharmacology & therapeutics.
[12] Lian-lian Wu,et al. 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. , 2020, Gastrointestinal endoscopy.
[13] Yun Lu,et al. Artificial intelligence system of faster region-based convolutional neural network surpassing senior radiologists in evaluation of metastatic lymph nodes of rectal cancer , 2019, Chinese medical journal.
[14] Ulas Bagci,et al. Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit. , 2020, Gastrointestinal endoscopy.
[15] Jing Cheng,et al. Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy. , 2019, Gastrointestinal endoscopy.
[16] M. Goetz,et al. Colonoscopic full-thickness resection using an over-the-scope device: a prospective multicentre study in various indications , 2017, Gut.
[17] Peng Li,et al. A deep neural network improves endoscopic detection of early gastric cancer without blind spots , 2019, Endoscopy.
[18] J. Sese,et al. Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy , 2019, Scientific Reports.
[19] Hayato Itoh,et al. Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience. , 2018, Gastroenterology.
[20] S. Gross,et al. Siri here, cecum reached, but please wash that fold: Will artificial intelligence improve gastroenterology? , 2020, Gastrointestinal endoscopy.
[21] K. Mori,et al. Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy , 2018, Annals of Internal Medicine.
[22] Artificial intelligence in endoscopy: the guardian angel is around the corner. , 2020, Gastrointestinal endoscopy.
[23] Eric J Topol,et al. High-performance medicine: the convergence of human and artificial intelligence , 2019, Nature Medicine.
[24] H. Kawachi,et al. Artificial intelligence diagnosis of Helicobacter pylori infection using blue laser imaging-bright and linked color imaging: a single-center prospective study , 2018, Annals of gastroenterology.
[25] Donald E. Brown,et al. Artificial Intelligence Applied to Gastrointestinal Diagnostics: A Review. , 2020, Journal of pediatric gastroenterology and nutrition.
[26] W. Leung,et al. Accuracy of artificial intelligence-assisted detection of upper GI lesions: a systematic review and meta-analysis. , 2020, Gastrointestinal endoscopy.
[27] C. Leggett,et al. Artificial intelligence in the age of cognitive endoscopy. , 2020, Gastrointestinal endoscopy.
[28] Eun Mi Song,et al. Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model , 2020, Scientific Reports.
[29] Kai Zhang,et al. Diagnosing chronic atrophic gastritis by gastroscopy using artificial intelligence. , 2020, Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver.
[30] Bing Hu,et al. Real-time automated diagnosis of precancerous lesion and early esophageal squamous cell carcinoma using a deep learning model (with videos). , 2019, Gastrointestinal endoscopy.
[31] Nicolas Chapados,et al. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model , 2017, Gut.
[32] T. Xia,et al. Use of artificial intelligence for detection of gastric lesions by magnetically controlled capsule endoscopy. , 2020, Gastrointestinal endoscopy.
[33] P. Baldi,et al. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. , 2018, Gastroenterology.
[34] T. Tada,et al. Artificial intelligence-based diagnostic system classifying gastric cancers and ulcers: comparison between the original and newly developed systems , 2020, Endoscopy.
[35] Keewon Shin,et al. Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy , 2020, Clinical endoscopy.
[36] Aymeric Histace,et al. GTCreator: a flexible annotation tool for image-based datasets , 2018, International Journal of Computer Assisted Radiology and Surgery.
[37] Yusuke Horiuchi,et al. Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging , 2019, Digestive Diseases and Sciences.
[38] S. Yalamarthi,et al. Missed Diagnoses in Patients with Upper Gastrointestinal Cancers , 2004, Endoscopy.
[39] Henry Horng-Shing Lu,et al. Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis. , 2017, Gastroenterology.
[40] M. Fujishiro,et al. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images , 2018, Gastric Cancer.
[41] Ying Jin,et al. Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study. , 2019, The Lancet. Oncology.
[42] Takuya Yamada,et al. Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma , 2020, Esophagus.
[43] T. Wittenberg,et al. Automated polyp detection in the colorectum: a prospective study (with videos). , 2019, Gastrointestinal endoscopy.
[44] S. Thakkar,et al. Artificial intelligence for real-time detection of early esophageal cancer: another set of eyes to better visualize. , 2020, Gastrointestinal endoscopy.
[45] V. Herasevich,et al. Artificial intelligence and computer simulation models in critical illness , 2020, World journal of critical care medicine.
[46] T. Berzin,et al. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study , 2019, Gut.
[47] Wei Zhou,et al. Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy , 2019, Gut.
[48] M. Byrne,et al. How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening. , 2020, Gastrointestinal endoscopy clinics of North America.
[49] Tomohiro Tada,et al. Detecting gastric cancer from video images using convolutional neural networks , 2018, Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society.
[50] Andrew Q. Ninh,et al. Prediction of Polyp Pathology Using Convolutional Neural Networks Achieves "Resect and Discard" Thresholds. , 2019, The American journal of gastroenterology.
[51] V. Kaul,et al. The history of artificial intelligence in medicine. , 2020, Gastrointestinal endoscopy.
[52] K. Koike,et al. Utilizing artificial intelligence in endoscopy: a clinician’s guide , 2020, Expert review of gastroenterology & hepatology.
[53] O. Hosokawa,et al. Difference in accuracy between gastroscopy and colonoscopy for detection of cancer. , 2007, Hepato-gastroenterology.
[54] Takumi Itoh,et al. Deep learning analyzes Helicobacter pylori infection by upper gastrointestinal endoscopy images , 2018, Endoscopy International Open.
[55] P. Millner,et al. Benefits of the use of blood conservation in scoliosis surgery , 2016, World journal of orthopedics.