2023
DOI: 10.3390/jcm12216721
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Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal Neoplasms

Magdalena Leśniewska,
Rafał Patryn,
Agnieszka Kopystecka
et al.

Abstract: Gastrointestinal cancers are characterized by high incidence and mortality. However, there are well-established methods of screening. The endoscopy exam provides the macroscopical image and enables harvesting the tissue samples for further histopathological diagnosis. The efficiency of endoscopies relies not only on proper patient preparation, but also on the skills of the personnel conducting the exam. In recent years, a number of reports concerning the application of artificial intelligence (AI) in medicine … Show more

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Cited by 4 publications
(2 citation statements)
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“…Recurrent neoplastic lesions may also harbor new molecular aberrations, distinct from the primary tumor, potentially leading to treatment resistance. 189 AI applications in this domain are primarily focused on the detection, characterization, and monitoring of tumors. A notable example is the AI-based model the artificial intelligence risk model (Mirai), which predicted 5-year cancer risk from screening mammograms with high accuracy, as demonstrated in a study involving 128 793 mammograms from 62 185 patients.…”
Section: Challenges and Future Perspectivesmentioning
confidence: 99%
“…Recurrent neoplastic lesions may also harbor new molecular aberrations, distinct from the primary tumor, potentially leading to treatment resistance. 189 AI applications in this domain are primarily focused on the detection, characterization, and monitoring of tumors. A notable example is the AI-based model the artificial intelligence risk model (Mirai), which predicted 5-year cancer risk from screening mammograms with high accuracy, as demonstrated in a study involving 128 793 mammograms from 62 185 patients.…”
Section: Challenges and Future Perspectivesmentioning
confidence: 99%
“…The integration of deep-learning techniques (DLT) in the realm of medical science, particularly within the context of coeliac disease diagnosis and management, has gained significant attention. Deep learning, a subfield of machine learning, has displayed remarkable potential in analyzing complex medical data, including endoscopic images, to discern significant patterns and diagnostic markers [7,8].…”
Section: Introductionmentioning
confidence: 99%