Innovative strategies for optimization of randomized therapeutic trials using molecular imaging and artificial intelligence
The prostate-specific membrane antigen (PSMA) is overexpressed in prostate cancer cells and can be utilized as a target structure to treat patients with advanced prostate cancer. PSMA therapy can display a high efficiency and prolong patients’ survival time; however, it is currently not clear which patients will benefit from therapy and which will not respond to it. This proposal therefore aims at optimizing the selection process for PSMA therapy by means of methods of artificial intelligence, characteristics of all metastases, and additional features. The findings can improve the understanding of prostate cancer. Furthermore, the methods developed via this proposal can equally be used to improve the image-based inclusion criteria of other cancerous entities which receive precision anti-cancer treatments.
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