Development of a model based on machine learning (AI) to help dependent people improve their quality of life

“In work carried out with Gaurav Kumar (India Institute of Information Technology Allahabad, India) and the URV (Universitat Rovira i Virgili), oriented towards Artificial Intelligence, merging the Quality of Life scale and the Support Intensity Scale (SIS; Scale Intensity Supports) quantitatively. The research under the direction of the IRD, on my part as an engineer and researcher in neuroscience at the UB (University of Barcelona), has allowed the development of an algorithm with which the Support Intensity has been defined from the Quality of Life deficiencies below the factor 100 (average and normal quality of life of the elderly group, with Mild and Medium Cognitive Impairment), and three very relevant invariable values ​​have been found, whose weight in the Quality of life for older people, adds up to 74% (Physical Well-being with 35%, Emotional Well-being with 35%, and Mental Well-being with 35%, and Emotional Well-being with 35%, respectively). 28% and Material Well-being with 11%).

These factors are also being corroborated in Mental Health Expert Patients, with the same quantification with the Pere Mata Institute. As they are Expert Patients (pharmacologically and psychologically in stable treatment), it allows us to generalize the results to the general population for their quality of life. This certifies the old assertion, “mens sana in corpore sana”, which Wikipedia qualifies, saying that the meaning in its day was: “balanced spirit, in a balanced body”, the nuance is not small, and the research carried out corroborates it. In addition, the Pre-Report for a preliminary Support Intensity is automatically edited when the Gencat-Inico Quality of Life scale is performed for the first time on a person, with a SWOT structure (Weaknesses, Threats, Strengths and Opportunities), with application in the Always With You project. of Mental Health and the Pere Mata Institute.”