TY - JOUR
T1 - Use of an artificial neural network to identify patient clusters in a large cohort of patients with melanoma by simultaneous analysis of costs and clinical characteristics
AU - Damiani, Giovanni
AU - Buja, Alessandra
AU - Grossi, Enzo
AU - Rivera, Michele
AU - De Polo, Anna
AU - De Luca, Giuseppe
AU - Zorzi, Manuel
AU - Vecchiato, Antonella
AU - Del Fiore, Paolo
AU - Saia, Mario
AU - Baldo, Vincenzo
AU - Rugge, Massimo
AU - Rossi, Carlo Riccardo
AU - Damiani, Gianfranco
AU - Damiani, Gianfranco
PY - 2020
Y1 - 2020
N2 - The incidence of cutaneous malignant melanoma (CMM) in Italy has increased in the last decade, leading to publichealth concern and rising costs of healthcare (1, 2). In addition to individual susceptibility to development of CMM, several environmental variables influence prognosis in this disease. These variables include social disparities, socioeconomic status, education and marital status (3). How ever, the impact of these variables on costs is unknown. The current study used a new methodology, based on an artificial neural network (ANN), to decodify this complexity by simultaneously describing the relation-ships between clinical, sociodemographic, outcome, and cost variables, and grouping patients into clusters (4, 5).
AB - The incidence of cutaneous malignant melanoma (CMM) in Italy has increased in the last decade, leading to publichealth concern and rising costs of healthcare (1, 2). In addition to individual susceptibility to development of CMM, several environmental variables influence prognosis in this disease. These variables include social disparities, socioeconomic status, education and marital status (3). How ever, the impact of these variables on costs is unknown. The current study used a new methodology, based on an artificial neural network (ANN), to decodify this complexity by simultaneously describing the relation-ships between clinical, sociodemographic, outcome, and cost variables, and grouping patients into clusters (4, 5).
KW - artificial neural networks
KW - costs
KW - cutaneous melanoma
KW - machine learning
KW - non-linear associations
KW - semantic connectivity map
KW - artificial neural networks
KW - costs
KW - cutaneous melanoma
KW - machine learning
KW - non-linear associations
KW - semantic connectivity map
UR - http://hdl.handle.net/10807/166288
U2 - 10.2340/00015555-3680
DO - 10.2340/00015555-3680
M3 - Article
SN - 1651-2057
VL - 100
SP - 1
EP - 3
JO - Acta Dermato-Venereologica
JF - Acta Dermato-Venereologica
ER -