The application of artificial intelligence in the medical field has increased significantly in recent decades. When diangosis requires long timelines and is strongly influenced by inter- and intra-operator variability, computer-aided diagnosis (CAD) systems have been developed that take advantage of machine learning (ML) and deep learning (DL) approaches to support physicians. Two of these areas are histopathology and dermatology, on which we have focused in our researches.
Hepatological and Dermatological Diagnostics with Artificial Intelligence / Grignaffini, Flavia; Barbuto, F.; Troiano, M.; Paloni, G.; Mangini, F.; Piazzo, L.; Cantisani, C.; De Stefanis, C.; Simeoni, P.; Alisi, A.; Frezza, F.. - (2024). (Intervento presentato al convegno Workshop “Multiscale Modeling and Engineering Applications” tenutosi a Roma).
Hepatological and Dermatological Diagnostics with Artificial Intelligence
Flavia Grignaffini;M. Troiano;G. Paloni;F. Mangini;L. Piazzo;C. Cantisani;C. De Stefanis;P. Simeoni;A. Alisi;F. Frezza
2024
Abstract
The application of artificial intelligence in the medical field has increased significantly in recent decades. When diangosis requires long timelines and is strongly influenced by inter- and intra-operator variability, computer-aided diagnosis (CAD) systems have been developed that take advantage of machine learning (ML) and deep learning (DL) approaches to support physicians. Two of these areas are histopathology and dermatology, on which we have focused in our researches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
