A multidimensional data decision support system based on fuzzy logic for risks prediction of elderly people living in nursing homes.

This project is focused on the reduction of adverse events in the elderly, describing the analysis of the main risk factors for old people living in nursing homes, the different techniques used to acquire the necessary information with a multidimensional approach, and the development of a prediction model based on an expert system, with the help of a Fuzzy Inference System (FIS). The developed model is tested on simulated data and compared with the evaluation of 8 clinicians give with the same premises. The results show how the judgment of the experts is consistent with the algorithm scores in the prediction of the occurrence of these risk conditions.

This project is focused on the reduction of adverse events in the elderly, describing the analysis of the main risk factors for old people living in nursing homes, the different techniques used to acquire the necessary information with a multidimensional approach, and the development of a prediction model based on an expert system, with the help of a Fuzzy Inference System (FIS). The developed model is tested on simulated data and compared with the evaluation that 8 clinicians give with the same premises. The results show how the judgment of the experts is consistent with the algorithm scores in the prediction of the occurrence of these risk conditions.