Every day, medical specialists analyze complex clinical cases and must make decisions that can negatively affect the well-being of their patients, the costs of procedures, the price of health insurance and the reputation of the specialists and medical systems involved, or even be fatal. The quest to improve healthcare procedures, especially in order to mitigate the risks of adverse events, has been one of the great challenges of our time, and the development of methods and computer systems that help specialists in the decision-making process has been growing in scientific and business circles. The main objective of this work was to propose a model to aid decision-making in clinical cases considering collective diagnosis, with the aim of mitigating the risks and uncertainties faced by medical specialists called Anais. The results obtained in experiments were statistically significant in terms of the applicability of the Anais model for the process of mitigating decision-making errors and as an educational tool.