Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual's risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AI-Mind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind's innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contributions.

Percepción estudiantil de la calidad educativa sobre las prácticas comunitarias / Students perceptions of the quality of education on community practices

Objetivo: Se pretende conocer la percepción de la calidad educativa sobre las prácticas comunitarias en los estudiantes de Enfermería en la Universidad de San Martín de Porres. Material y método: La calidad educativa es evaluada a través de cuatro factores: sede de práctica, desempeño docente, relaciones interpersonales y aprendizaje teoría/práctica. La muestra fue de 174 estudiantes. Se optó por un diseño no experimental, descriptivo-comparativo. El instrumento empleado fue elaborado siguiendo la metodología de Likert. Comprende 37 reactivos con cinco anclajes de respuestas cada uno. Tiene como soporte la validez de contenido y la fiabilidad de Alpha de Crombach de 0,94. Resultados: Los estudiantes se muestran satisfechos; le dan un calificativo entre bueno y excelente. Perciben que las prácticas comunitarias consolidan sus conocimientos teóricos, reconocen la capacidad del docente en una situación de práctica comunitaria, están preparados para interactuar con el entorno comunitario y esperan de la sede mejores condiciones tecnológicas y físicas. Conclusiones: Conforme avanzan los ciclos, se incrementa la capacidad crítica de los estudiantes y crecen sus expectativas sobre las prácticas.

Objective: The aim is to study the perceptions of the quality of education on community practices in the nursing students at the University of San Martin de Porres. Material and method: The quality of education is evaluated through four factors: Headquarters practice, teacher performance, interpersonal relationships and learning theory / practice. The sample was made up of 174 students. It opted for a non-experimental design, descriptive-comparative. The instrument used was developed following the methodology of Likert, 37 reagents comprising five anchorages answers each. It supports the content validity and reliability of Alpha Crombach of 0.94. Results: Students are shown Satisfied give a qualifier between good and excellent. They feel community practices consolidate their knowledge, recognize the ability of the teacher in a situation of Community practice, are ready to interact with the community environment and expect from the headquarters, better physical and technological conditions. Conclusions: According progressing cycles, increases the critical capacity of the students and grows their expectations on the practice.