Techniques to integrate artificial intelligence systems with medical information in gastroenterology

Techniques to integrate artificial intelligence systems with medical information in gastroenterology

[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.