Colorectal cancer is the third most common tumor in men and the second in women, accounting for 10% of all tumors worldwide. It ranks second in cancer-related deaths with 9.4%, following lung cancer. The decrease in mortality rate documented over the last 20 years has shown signs of slowing down since 2017, necessitating concentrated actions on specific measures that have exhibited considerable potential. As such, the technical foundation and research evidence for blood-derived protein markers have been set, pending comparative validation, clinical implementation and integration into an artificial intelligence enabled decision support framework that also considers knowledge on risk factors. The current paper aspires to constitute the driving force for creating change in colorectal cancer screening by reviewing existing medical practices through accessible and non-invasive risk estimation, employing a straightforward artificial intelligence outlook.

An Artificial Intelligence Outlook for Colorectal Cancer Screening / P. Katrakazas, A. Ballas, M. Anisetti, I. Spais - In: 2022 IEEE Eighth International Conference on Big Data Computing Service and Applications (BigDataService)[s.l] : IEEE, 2022. - ISBN 978-1-6654-5890-0. - pp. 66-72 (( Intervento presentato al 8. convegno International Conference on Big Data Computing Service and Applications (BigDataService) tenutosi a Newark nel 2022 [10.1109/BigDataService55688.2022.00018].

An Artificial Intelligence Outlook for Colorectal Cancer Screening

M. Anisetti;
2022

Abstract

Colorectal cancer is the third most common tumor in men and the second in women, accounting for 10% of all tumors worldwide. It ranks second in cancer-related deaths with 9.4%, following lung cancer. The decrease in mortality rate documented over the last 20 years has shown signs of slowing down since 2017, necessitating concentrated actions on specific measures that have exhibited considerable potential. As such, the technical foundation and research evidence for blood-derived protein markers have been set, pending comparative validation, clinical implementation and integration into an artificial intelligence enabled decision support framework that also considers knowledge on risk factors. The current paper aspires to constitute the driving force for creating change in colorectal cancer screening by reviewing existing medical practices through accessible and non-invasive risk estimation, employing a straightforward artificial intelligence outlook.
colorectal cancer; screening; risk factor analysis; artificial intelligence approach
Settore INF/01 - Informatica
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/962076
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