Background: Artificial Intelligence (AI) and digital therapeutics (DTx) have emerged as transformative technologies in oncology, particularly in predicting and optimizing treatment responses.AI, through machine learning (ML) and deep learning (DL), has revolutionized early detection, precision medicine, and therapeutic decision-making.This study aimed to assess the efficacy of AI-driven predictive models in predicting cancer treatment responses, with a focus on breast cancer.Methods: A systematic review and meta-analysis were conducted, evaluating AI applications in predicting treatment responses for chemotherapy, immunotherapy, and targeted therapies.Studies were selected based on their use of AI models, including ML and DL algorithms, and clinical validation in prospective cohorts or randomized controlled trials (RCTs).A total of 32 studies published between 2015 and 2023, involving over 12,000 patients, were included.
Kridis et al. (Wed,) studied this question.