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Artificial Intelligence in Coloproctology: A Review of Emerging Technologies and Clinical Applications. | LitMetric

AI Article Synopsis

  • AI is revolutionizing gastroenterology, particularly in coloproctology, by improving diagnosis, treatment, and overall patient care.
  • Notable applications include colonoscopy, where AI helps detect polyps and early signs of colorectal cancer, and capsule endoscopy, which ensures quick and accurate video readings for various anomalies.
  • The article reviews current AI implementations in coloproctology and discusses potential future developments in the field.

Article Abstract

Artificial intelligence (AI) has emerged as a transformative tool across several specialties, namely gastroenterology, where it has the potential to optimize both diagnosis and treatment as well as enhance patient care. Coloproctology, due to its highly prevalent pathologies and tremendous potential to cause significant mortality and morbidity, has drawn a lot of attention regarding AI applications. In fact, its application has yielded impressive outcomes in various domains, colonoscopy being one prominent example, where it aids in the detection of polyps and early signs of colorectal cancer with high accuracy and efficiency. With a less explored path but equivalent promise, AI-powered capsule endoscopy ensures accurate and time-efficient video readings, already detecting a wide spectrum of anomalies. High-resolution anoscopy is an area that has been growing in interest in recent years, with efforts being made to integrate AI. There are other areas, such as functional studies, that are currently in the early stages, but evidence is expected to emerge soon. According to the current state of research, AI is anticipated to empower gastroenterologists in the decision-making process, paving the way for a more precise approach to diagnosing and treating patients. This review aims to provide the state-of-the-art use of AI in coloproctology while also reflecting on future directions and perspectives.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11477032PMC
http://dx.doi.org/10.3390/jcm13195842DOI Listing

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