Quality Assurance and Testing Strategies in a Digital Platform for Screening and Early Diagnosis of Oral Cancer - Pedrosa, Leandro; Costa, Luiza de Oliveira; Freitas, Gabriel; Barbosa, Tallya Jesus Sousa; Barbosa, Giovanna Vargas; Braga, Renata Dutra; Ribeiro-Rotta, Rejane F. (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI); 2026: Anais do XXII Simpósio Brasileiro de Sistemas de InformaçãoDO - 10.5753/sbsi.2026.248359, 2026)
Research Context: Software testing in healthcare systems is critical, as failures can compromise diagnoses, professional trust and patient safety. In severe conditions, such as oral cancer, the absence of robust validation strategies may lead to delays or clinical errors with serious consequences. Scientific and/or Practical Problem: Despite advances in AI-based healthcare platforms, gaps remain in the adoption of integrated testing strategies that ensure quality, usability, and security in critical systems. These shortcomings can hinder the reliability of AI-driven tools in clinical environments. Proposed Solution and/or Analysis: This study reports the testing practices applied in the Sobre-Vidas Platform-“Oral Cancer”, designed to support early diagnosis through AI. A multidimensional testing strategy was implemented, encompassing back-end (unit, integration, performance, and security) and front-end testing (usability, responsiveness, accessibility and functional), supported by tools including Python, JUnit, SonarQube, Locust, and Cypress. Related IS Theory: The work is grounded in software quality models, particularly ISO/IEC 25010, and in socio-technical system theory, which emphasizes the interplay between technical reliability and user acceptance within digital health environments. Research Method: A qualitative case study approach was adopted, combining practices such as test driven development (TDD) and automated API testing with validation in real world healthcare contexts. Trials were conducted with physicians, dentists, and health secretaries in two municipalities in the state of Goiás, with feedback collected through observation, interviews, and usability sessions. Summary of Results: The need for adjustments in workflows, terminology, and interface design was revealed, highlighting that continuous and integrated testing processes are essential for ensuring clinical effectiveness, safety, and system adoption. Contributions and Impact to IS Area: This work demonstrates how integrated testing strategies, aligned with established quality frameworks, can enhance trust and adoption of AI-driven healthcare platforms. It broadens the discussion on software testing as a socio-technical enabler of safety and innovation in digital health.