HARNESSING NEURAL NETWORK DISCOVERED CORRELATIONS IN MEDICINE TO OPTIMIZE PATIENT TREATMENT

Abstract

Without requiring knowledge of pre-existing population-driven data, phenotypic medicine platforms (PPMs) such as CURATE.AI were employed. These recommendations were based on predictions provided by the patient’s own treatment profile longitudinally. First, a prospective feasibility trial has been conducted to guide and modulate Ibrutinib doses for Waldenström’s macroglobulinemia with CURATEAI. Using the methodology of this study as a basis, a perspective piece is provided on how PPMs can be integrated with radiation oncology, and the possible implementation of a CURATE.AI-guided radiotherapy. Lastly, the aims, hypotheses, and methods of an in vitro CURATE.AI-guided radiation therapy study are provided. In this thesis, PPMs such as CURATE.AI have demonstrated their feasibility and potential in personalizing treatment for oncology.