2020
DOI: 10.1097/mpg.0000000000002507
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Artificial Intelligence Applied to Gastrointestinal Diagnostics

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… Show more

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Cited by 28 publications
(16 citation statements)
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“…Currently, one of the most popular area of AI applications is the healthcare with the ultimate aims of increasing the quality of care, decreasing the cost, optimizing the workflow, achieving more efficient individualized care and precision medicine, and decreasing the need for human workforce in this most costly service sector in the world with an ever ageing population. There are many AI algorithms claiming to serve almost in each medical discipline [10][11][12][13][14][15][16][17][18], but initial efforts were heavily directed to diagnostic radiology which has many monotonous repetitive tasks in daily practice including diagnostic assessment of screening mammography and chest Xrays in which AI could easily separate "normal" from "abnormal." With the newer algorithms, AI is experimented in solving more complex problems and sophisticatedly assessing more detailed diagnostic studies including computed tomography and magnetic resonance imaging.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, one of the most popular area of AI applications is the healthcare with the ultimate aims of increasing the quality of care, decreasing the cost, optimizing the workflow, achieving more efficient individualized care and precision medicine, and decreasing the need for human workforce in this most costly service sector in the world with an ever ageing population. There are many AI algorithms claiming to serve almost in each medical discipline [10][11][12][13][14][15][16][17][18], but initial efforts were heavily directed to diagnostic radiology which has many monotonous repetitive tasks in daily practice including diagnostic assessment of screening mammography and chest Xrays in which AI could easily separate "normal" from "abnormal." With the newer algorithms, AI is experimented in solving more complex problems and sophisticatedly assessing more detailed diagnostic studies including computed tomography and magnetic resonance imaging.…”
Section: Introductionmentioning
confidence: 99%
“…Using AI-based algorithms has previously been attempted to assist clinicians in decision-making during medical procedures (113). More broadly and outside of surgery, AI and expert systems have been developed for the diagnosis and prognosis of several pathologies (114,115). In this context, AI models have been used to predict a condition on the basis of pretrained networks on data sets of medical records (e.g., radiology ultrasound and physiological profiles).…”
Section: Artificial Intelligencementioning
confidence: 99%
“…SVMs are models for classifying sets of data by creating a line or plane to separate data into distinct classes. This allows the machine to then classify new input data based on previously input data [ 41 , 42 ].…”
Section: Artificial Intelligence: General Information and Terminologymentioning
confidence: 99%