New advances in artificial intelligence for the diagnosis and treatment of colorectal cancer: a literature review
Journal
Sapienza: International Journal of Interdisciplinary Studies
ISSN
2675-9780
Date Issued
2024-02-07
Author(s)
Raul Jonathan Ríos Quinte
Alisson Berenice Ortiz Osorio
César David Toaquiza Toapanta
Elsa Alicia Landi Faican
Jefferson Alexander García Toala
Abstract
Introduction: With 1.93 million new instances of colorectal cancer (CRC) reported in 2020, the disease presents a danger to world health. With its potential to improve CRC management, artificial intelligence (AI) has become increasingly prominent in the medical field. This research attempts to evaluate the current status of AI applications in CRC diagnosis and treatment, considering regional differences in healthcare systems and populations.
Methodology: On databases like ScienceDirect, Google Scholar, and PubMed, a systematic literature evaluation was carried out using search phrases including "artificial intelligence," "colorectal cancer," "diagnosis," and "treatment." English-language research on AI applications in CRC diagnosis and treatment that were published during the previous five years met the inclusion criteria.
Results: Endoscopic, non-invasive, histological, and radiographic techniques are among the AI applications used in CRC diagnosis. Prognostic forecasts, diagnostic accuracy, and tumor segmentation are all significantly enhanced by AI. AI helps with targeted therapy and chemoradiotherapy decision-making, improves surgical accuracy, and helps with personalized regimens.
Conclusion: The use of AI in colorectal cancer management has the potential for timely identification, precise diagnosis, and customized care. Continuous developments in AI algorithms and clinical data support the development of precision medicine, which offers significant gains in CRC treatment and detection.
Methodology: On databases like ScienceDirect, Google Scholar, and PubMed, a systematic literature evaluation was carried out using search phrases including "artificial intelligence," "colorectal cancer," "diagnosis," and "treatment." English-language research on AI applications in CRC diagnosis and treatment that were published during the previous five years met the inclusion criteria.
Results: Endoscopic, non-invasive, histological, and radiographic techniques are among the AI applications used in CRC diagnosis. Prognostic forecasts, diagnostic accuracy, and tumor segmentation are all significantly enhanced by AI. AI helps with targeted therapy and chemoradiotherapy decision-making, improves surgical accuracy, and helps with personalized regimens.
Conclusion: The use of AI in colorectal cancer management has the potential for timely identification, precise diagnosis, and customized care. Continuous developments in AI algorithms and clinical data support the development of precision medicine, which offers significant gains in CRC treatment and detection.