Literature DB >> 31567886

Artificial Intelligence Applied to Gastrointestinal Diagnostics: A Review.

Vatsal Patel1, Marium N Khan2, Aman Shrivastava3, Kamran Sadiq4, S Asad Ali4, Sean R Moore2, Donald E Brown3,5, Sana Syed2,4.   

Abstract

Artificial intelligence (AI), a discipline encompassed by data science, has seen recent rapid growth in its application to healthcare and beyond, and is now an integral part of daily life. Uses of AI in gastroenterology include the automated detection of disease and differentiation of pathology subtypes and disease severity. Although a majority of AI research in gastroenterology focuses on adult applications, there are a number of pediatric pathologies that could benefit from more research. As new and improved diagnostic tools become available and more information is retrieved from them, AI could provide physicians a method to distill enormous amounts of data into enhanced decision-making and cost saving for children with digestive disorders. This review provides a broad overview of AI and examples of its possible applications in pediatric gastroenterology.

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Year:  2020        PMID: 31567886      PMCID: PMC6934912          DOI: 10.1097/MPG.0000000000002507

Source DB:  PubMed          Journal:  J Pediatr Gastroenterol Nutr        ISSN: 0277-2116            Impact factor:   3.288


  49 in total

1.  Wireless capsule endoscopy.

Authors:  G Iddan; G Meron; A Glukhovsky; P Swain
Journal:  Nature       Date:  2000-05-25       Impact factor: 49.962

2.  Appearance of enhanced tissue features in narrow-band endoscopic imaging.

Authors:  Kazuhiro Gono; Takashi Obi; Masahiro Yamaguchi; Nagaaki Ohyama; Hirohisa Machida; Yasushi Sano; Shigeaki Yoshida; Yasuo Hamamoto; Takao Endo
Journal:  J Biomed Opt       Date:  2004 May-Jun       Impact factor: 3.170

3.  Augmenting capsule endoscopy diagnosis: a similarity learning approach.

Authors:  S Seshamani; R Kumar; T Dassopoulos; G Mullin; G Hager
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

4.  Automated Marsh-like classification of celiac disease in children using local texture operators.

Authors:  A Vécsei; G Amann; S Hegenbart; M Liedlgruber; A Uhl
Journal:  Comput Biol Med       Date:  2011-04-21       Impact factor: 4.589

5.  Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.

Authors:  Daniel Shu Wei Ting; Carol Yim-Lui Cheung; Gilbert Lim; Gavin Siew Wei Tan; Nguyen D Quang; Alfred Gan; Haslina Hamzah; Renata Garcia-Franco; Ian Yew San Yeo; Shu Yen Lee; Edmund Yick Mun Wong; Charumathi Sabanayagam; Mani Baskaran; Farah Ibrahim; Ngiap Chuan Tan; Eric A Finkelstein; Ecosse L Lamoureux; Ian Y Wong; Neil M Bressler; Sobha Sivaprasad; Rohit Varma; Jost B Jonas; Ming Guang He; Ching-Yu Cheng; Gemmy Chui Ming Cheung; Tin Aung; Wynne Hsu; Mong Li Lee; Tien Yin Wong
Journal:  JAMA       Date:  2017-12-12       Impact factor: 56.272

6.  Assessment of Crohn's disease lesions in wireless capsule endoscopy images.

Authors:  Rajesh Kumar; Qian Zhao; Sharmishtaa Seshamani; Gerard Mullin; Gregory Hager; Themistocles Dassopoulos
Journal:  IEEE Trans Biomed Eng       Date:  2011-10-18       Impact factor: 4.538

7.  Detection of small bowel polyps and ulcers in wireless capsule endoscopy videos.

Authors:  Alexandros Karargyris; Nikolaos Bourbakis
Journal:  IEEE Trans Biomed Eng       Date:  2011-05-16       Impact factor: 4.538

8.  Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.

Authors:  Teng Zhou; Guoqiang Han; Bing Nan Li; Zhizhe Lin; Edward J Ciaccio; Peter H Green; Jing Qin
Journal:  Comput Biol Med       Date:  2017-04-08       Impact factor: 4.589

Review 9.  Environmental Enteric Dysfunction in Children.

Authors:  Sana Syed; Asad Ali; Christopher Duggan
Journal:  J Pediatr Gastroenterol Nutr       Date:  2016-07       Impact factor: 2.839

10.  Classification of Paediatric Inflammatory Bowel Disease using Machine Learning.

Authors:  E Mossotto; J J Ashton; T Coelho; R M Beattie; B D MacArthur; S Ennis
Journal:  Sci Rep       Date:  2017-05-25       Impact factor: 4.379

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  6 in total

1.  Artificial intelligence and radiomics in nuclear medicine: potentials and challenges.

Authors:  Cumali Aktolun
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-12       Impact factor: 9.236

Review 2.  Artificial Intelligence and Its Role in Identifying Esophageal Neoplasia.

Authors:  Taseen Syed; Akash Doshi; Shan Guleria; Sana Syed; Tilak Shah
Journal:  Dig Dis Sci       Date:  2020-10-15       Impact factor: 3.199

3.  Artificial Intelligence-based Analytics for Diagnosis of Small Bowel Enteropathies and Black Box Feature Detection.

Authors:  Sana Syed; Lubaina Ehsan; Aman Shrivastava; Saurav Sengupta; Marium Khan; Kamran Kowsari; Shan Guleria; Rasoul Sali; Karan Kant; Sung-Jun Kang; Kamran Sadiq; Najeeha T Iqbal; Lin Cheng; Christopher A Moskaluk; Paul Kelly; Beatrice C Amadi; Syed Asad Ali; Sean R Moore; Donald E Brown
Journal:  J Pediatr Gastroenterol Nutr       Date:  2021-06-01       Impact factor: 3.288

Review 4.  Potential for Standardization and Automation for Pathology and Endoscopy in Inflammatory Bowel Disease.

Authors:  Sana Syed; Ryan W Stidham
Journal:  Inflamm Bowel Dis       Date:  2020-09-18       Impact factor: 7.290

Review 5.  Role of Artificial Intelligence in Video Capsule Endoscopy.

Authors:  Ioannis Tziortziotis; Faidon-Marios Laskaratos; Sergio Coda
Journal:  Diagnostics (Basel)       Date:  2021-06-30

Review 6.  Evolution in the Practice of Pediatric Endoscopy and Sedation.

Authors:  Conrad B Cox; Trevor Laborda; J Matthew Kynes; Girish Hiremath
Journal:  Front Pediatr       Date:  2021-07-14       Impact factor: 3.418

  6 in total

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