How artificial intelligence revolutionizes the world of multiple myeloma

Abstract

Multiple myeloma is the second most frequent hematologic malignancy worldwide with high morbidity and mortality. Although it is considered an incurable disease, the enhanced understanding of this neoplasm has led to new treatments, which have improved patients’ life expectancy. Large amounts of data have been generated through different studies in the settings of clinical trials, prospective registries, and real-world cohorts, which have incorporated laboratory tests, flow cytometry, molecular markers, cytogenetics, diagnostic images, and therapy into routine clinical practice. In this review, we described how these data can be processed and analyzed using different models of artificial intelligence, aiming to improve accuracy and translate into clinical benefit, allow a substantial improvement in early diagnosis and response evaluation, speed up analyses, reduce labor-intensive process prone to operator bias, and evaluate a greater number of parameters that provide more precise information. Furthermore, we identified how artificial intelligence has allowed the development of integrated models that predict response to therapy and the probability of achieving undetectable measurable residual disease, progression-free survival, and overall survival leading to better clinical decisions, with the potential to inform on personalized therapy, which could improve patients’ outcomes. Overall, artificial intelligence has the potential to revolutionize multiple myeloma care, being necessary to validate in prospective clinical cohorts and develop models to incorporate into routine daily clinical practice.