Artificial intelligence-based medical decision-making systems can significantly accelerate decision processes and enhance accuracy.However,challenges persist in achieving personalized care and in the compre-hensive collection of medical data.This paper explores potential solutions to these issues by examining AI ap-plications in diagnostic omics and multi-dimensional data acquisition,providing an overview of current pro-gress and limitations in developing intelligent medical decision systems through these approaches.Additional-ly,the paper also discusses the broad potential for artificial intelligence applications in medical education and their possible contributions to advancing overall decision-making standards in healthcare.