ANALYSIS AND PROTOTYPE OF AN INTELLIGENT SYSTEM FOR GENERATION AND PERSONALIZATION OF CLINICAL CASES IN HEALTH EDUCATION

This paper presents the analysis and prototyping of an intelligent system for generation, personalization and evaluation of clinical cases in health education. It is based on the observation that clinical training faces limitations in terms of the diversity of scenarios, availability of patients and the offer of immediate feedback, which hinders the development of clinical reasoning and the objective evaluation of students. The main objective was to analyze requirements and design interface prototypes for a platform that automates the creation of cases, allows their customization by the teacher and offers formative feedback in near real time. It is characterized as an applied, qualitative and descriptive study: the requirements were raised through semi-structured interviews and direct observation with professionals from the Teaching Clinic of the Santo Agostinho University Center (UNIFSA) and the prototypes were elaborated in Figma with preliminary validation by professors and supervisors. As a result, functional and non-functional requirements were specified, a flowchart of the flow of use was elaborated and prototypes were produced that include AI-assisted generation, teacher editing (human-in-the-loop), resolution by the student, automatic feedback and performance reports. It is concluded that the proposal is conceptually feasible and justifies the following step: development of the platform, curatorship of local corpus, obtaining ethical approvals and implementation of a pilot in the Santo Agostinho Teaching Clinic for evaluation of pedagogical and operational impact.