Artificial Intelligence and Advanced Melanoma: Treatment Management Implications
Antonino Guerrisi,
Italia Falcone,
Fabio Valenti,
Marco Rao,
Enzo Gallo,
Sara Ungania,
Maria Teresa Maccallini,
Maurizio Fanciulli,
Pasquale Frascione,
Aldo Morrone,
Mauro Caterino
Affiliations
Antonino Guerrisi
Radiology and Diagnostic Imaging Unit, Department of Clinical and Dermatological Research, San Gallicano Dermatological Institute IRCCS, 00144 Rome, Italy
Italia Falcone
SAFU, Department of Research, Advanced Diagnostics, and Technological Innovation, IRCCS-Regina Elena National Cancer Institute, 00144 Rome, Italy
Fabio Valenti
UOC Oncological Translational Research, IRCCS-Regina Elena National Cancer Institute, 00144 Rome, Italy
Marco Rao
Enea-FSN-TECFIS-APAM, C.R. Frascati, via Enrico Fermi, 45, 00146 Rome, Italy
Enzo Gallo
Pathology Unit, IRCCS-Regina Elena National Cancer Institute, 00144 Rome, Italy
Sara Ungania
Medical Physics and Expert Systems Laboratory, Department of Research and Advanced Technologies, IRCCS-Regina Elena Institute, 00144 Rome, Italy
Maria Teresa Maccallini
Departement of Clinical and Molecular Medicine, Università La Sapienza di Roma, 00185 Rome, Italy
Maurizio Fanciulli
SAFU, Department of Research, Advanced Diagnostics, and Technological Innovation, IRCCS-Regina Elena National Cancer Institute, 00144 Rome, Italy
Scientific Direction, San Gallicano Dermatological Institute IRCCS, 00144 Rome, Italy
Mauro Caterino
Radiology and Diagnostic Imaging Unit, Department of Clinical and Dermatological Research, San Gallicano Dermatological Institute IRCCS, 00144 Rome, Italy
Artificial intelligence (AI), a field of research in which computers are applied to mimic humans, is continuously expanding and influencing many aspects of our lives. From electric cars to search motors, AI helps us manage our daily lives by simplifying functions and activities that would be more complex otherwise. Even in the medical field, and specifically in oncology, many studies in recent years have highlighted the possible helping role that AI could play in clinical and therapeutic patient management. In specific contexts, clinical decisions are supported by “intelligent” machines and the development of specific softwares that assist the specialist in the management of the oncology patient. Melanoma, a highly heterogeneous disease influenced by several genetic and environmental factors, to date is still difficult to manage clinically in its advanced stages. Therapies often fail, due to the establishment of intrinsic or secondary resistance, making clinical decisions complex. In this sense, although much work still needs to be conducted, numerous evidence shows that AI (through the processing of large available data) could positively influence the management of the patient with advanced melanoma, helping the clinician in the most favorable therapeutic choice and avoiding unnecessary treatments that are sure to fail. In this review, the most recent applications of AI in melanoma will be described, focusing especially on the possible finding of this field in the management of drug treatments.