The invention relates to the technical field of decision support, in particular to a
pelvic organ prolapse
disease preoperative doctor-patient joint decision
evaluation system based on
artificial intelligence, which comprises an initial inquiry acquisition module, a communication behavior and expression evaluation module, a
cognition test module, a patient feature analysis module and a decision communication module. According to the method, through structural induction of multi-dimensional
health data,
subjective feeling and psychological states of patients are meticulously quantified, interaction features and knowledge understanding short boards in the communication process are actively mined,
label type feature affiliation is automatically generated, and self-adaptive information matching for individual characteristics and risk features is achieved; the method cooperatively promotes efficient fusion of willingness,
cognition and schemes between doctors and patients, enhances participation and continuous tracking ability of the whole diagnosis and treatment process, optimizes pertinence of joint decision, strengthens dynamic
information feedback, accurately recognizes weak links and specific appeals, supports high-
level data closed-loop and behavior tracking, and further promotes scientific decision and improves patient experience.