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Machine Learning in Oncology:A Clinical Appraisal - 2020

Machine Learning In Oncology:A Clinical Appraisal

Research Area:  Machine Learning

Abstract:

Machine learning (ML) is a branch of artificial intelligence centered on algorithms which do not need explicit prior programming to function but automatically learn from available data, creating decision models to complete tasks. ML-based tools have numerous promising applications in several fields of medicine. Its use has grown following the increased availability of patient data due to technological advances such as digital health records and high-volume information extraction from medical images. Multiple ML algorithms have been proposed for applications in oncology. For instance, they have been employed for oncological risk assessment, automated segmentation, lesion detection, characterization, grading and staging, prediction of prognosis and therapy response. In the near future, ML could become essential part of every step of oncological screening strategies and patients’ management thus leading to precision medicine.

Keywords:  

Author(s) Name:  Renato Cuocolo, Martina Caruso, Teresa Perillo, Lorenzo Ugga, Mario Petretta

Journal name:  Cancer Letters

Conferrence name:  

Publisher name:  Elsevier

DOI:  10.1016/j.canlet.2020.03.032

Volume Information:  Volume 481, 1 July 2020, Pages 55-62