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Crohn's disease manifesting as an isolated cecal polyp and secondary appendiceal obstruction with histologically normal bowel.

Authors:
Jurgen Gerada Elaine Borg Matthew Cassar James DeGaetano Godfrey LaFerla Mario Vassallo

Int J Colorectal Dis 2014 Oct 21;29(10):1307-8. Epub 2014 May 21.

Division of Gastroenterology, Mater Dei Hospital, Msida, Malta,

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http://dx.doi.org/10.1007/s00384-014-1905-zDOI Listing
October 2014

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The effect of train-the-colonoscopy-trainer course on colonoscopy quality indicators.

Authors:
Geir Hoff Edoardo Botteri Gert Huppertz-Hauss Jan Magnus Kvamme Øyvind Holme Lars Aabakken Stein Dahler Asle W Medhus Ingrid Blomgren Per Sandvei Ole Darre-Næss Øystein Kjellevold Birgitte Seip

Endoscopy 2021 Feb 23. Epub 2021 Feb 23.

Cancer Registry of Norway, Oslo, Norway.

Background:  Systematic training in colonoscopy is highly recommended; however, we have limited knowledge of the effects of "training-the-colonoscopy-trainer" (TCT) courses. Using a national quality register on colonoscopy performance, we aimed to evaluate the effects of TCT participation on defined quality indicators.

Methods:  This observational study compared quality indicators (pain, cecal intubation, and polyp detection) between centers participating versus not participating in a TCT course. Read More

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February 2021
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A novel machine learning-based algorithm to identify and classify lesions and anatomical landmarks in colonoscopy images.

Authors:
Ying-Chun Jheng Yen-Po Wang Hung-En Lin Kuang-Yi Sung Yuan-Chia Chu Huann-Sheng Wang Jeng-Kai Jiang Ming-Chih Hou Fa-Yauh Lee Ching-Liang Lu

Surg Endosc 2021 Feb 16. Epub 2021 Feb 16.

Endoscopy Center for Diagnosis and Treatment, Taipei Veterans General Hospital, Taipei, Taiwan.

Objectives: Computer-aided diagnosis (CAD)-based artificial intelligence (AI) has been shown to be highly accurate for detecting and characterizing colon polyps. However, the application of AI to identify normal colon landmarks and differentiate multiple colon diseases has not yet been established. We aimed to develop a convolutional neural network (CNN)-based algorithm (GUTAID) to recognize different colon lesions and anatomical landmarks. Read More

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February 2021
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Wavelet Transform and Deep Convolutional Neural Network-Based Smart Healthcare System for Gastrointestinal Disease Detection.

Authors:
Subhashree Mohapatra Janmenjoy Nayak Manohar Mishra Girish Kumar Pati Bignaraj Naik Tripti Swarnkar

Interdiscip Sci 2021 Feb 10. Epub 2021 Feb 10.

Department of Computer Application, Siksha O Anusandhan (Deemed to Be University), Bhubaneswar, 751030, India.

This work presents a smart healthcare system for the detection of various abnormalities present in the gastrointestinal (GI) region with the help of time-frequency analysis and convolutional neural network. In this regard, the KVASIR V2 dataset comprising of eight classes of GI-tract images such as Normal cecum, Normal pylorus, Normal Z-line, Esophagitis, Polyps, Ulcerative Colitis, Dyed and lifted polyp, and Dyed resection margins are used for training and validation. The initial phase of the work involves an image pre-processing step, followed by the extraction of approximate discrete wavelet transform coefficients. Read More

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February 2021
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Predictive factors for adenoma detection rates: a video study of endoscopist practices.

Authors:
Sun Young Yang Susan Y Quan Shai Friedland Jennifer Y Pan

Endosc Int Open 2021 Feb 3;9(2):E216-E223. Epub 2021 Feb 3.

Veterans Affairs Palo Alto Health Care System, Palo Alto, California, United States.

 In 2015, the American Society for Gastrointestinal Endoscopy (ASGE) and American College of Gastroenterology (ACG) Task Force on Quality in Endoscopy deemed adenoma detection rate (ADR) the most important quality measure for colonoscopy. There has been much interest in factors that can increase ADR. To date, however, few studies have looked at what intra-procedural endoscopist practices are associated with improving ADR. Read More

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February 2021
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Combined endoscopic and laparoscopic surgery for the treatment of complex benign colonic polyps (CELS): observational study.

Authors:
Xavier Serra-Aracil Esther Gil-Barrionuevo Eva Martinez Laura Mora-López Anna Pallisera-Lloveras Sheila Serra-Pla Valenti Puig-Divi Salvador Navarro-Soto

Cir Esp 2021 Jan 20. Epub 2021 Jan 20.

Unidad de Cirugía Colorrectal, Departamento de Cirugía General y Ap Digestivo, Hospital Universitari Parc Taulí, Universitat Autonoma de Barcelona (UAB), Barcelona, España.

Purpose: Combined endoscopic and laparoscopic surgery (CELS) has emerged as a promising method for managing complex benign lesions that would otherwise require major colonic resection. The aim of this study was to describe the different techniques and to evaluate the safety of CELS, assess its outcomes in a technique that is scarcely widespread in our environment.

Method: Observational retrospective study, short-term outcomes of patients undergoing CELS for benign colon polyps from October 2018 to June 2020 were evaluated. Read More

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January 2021
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