Artificial Intelligence/Machine Learning and Mechanistic Modeling Approaches as Translational Tools to Advance Personalized Medicine Decisions

Nowadays, advancements in omics-based methodologies, data analysis, informatics, and bioinformatics, as well as nanotechnology have continuously led to a more digitized, robust, as well as information-based environment in biomedicine and health care. Precision in therapy will be ensured through the application of computerized platforms, as well as interdisciplinary integrated analysis and decision-making. In this review, artificial intelligence/machine learning approaches and mechanistic modeling methodologies will be discussed as translational tools aiming to advance personalized medicine decisions and patient care.