Development of an Artificial Intelligence Model for Optimising Therapy in Gliomas Gliomas

Artificial intelligence (AI) undoubtedly represents the main tool currently available in the definition of complex algorithms and its use in the medical field is becoming increasingly strategic.As reported in the literature, it is increasingly difficult to find new therapeutic strategies for neoplasms, especially neurological ones. Molecular characterisation is therefore increasingly essential, as is the use of new predictive methods. With this in mind, the aim of this study is to assess, by means of AI algorithms applied to genomic data, in what percentage molecular alterations are susceptible to potential drug therapies, compared to the literature data that does not consider AI algorithms for this purpose.

Artificial intelligence (AI) undoubtedly represents the main tool currently available in the definition of complex algorithms and its use in the medical field is becoming increasingly strategic.As reported in the literature, it is increasingly difficult to find new therapeutic strategies for neoplasms, especially neurological ones. Molecular characterisation is therefore increasingly essential, as is the use of new predictive methods. With this in mind, the aim of this study is to assess, by means of AI algorithms applied to genomic data, in what percentage molecular alterations are susceptible to potential drug therapies, compared to the literature data that does not consider AI algorithms for this purpose.