Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment

BMC Psychiatry, Journal Year: 2025, Volume and Issue: 25(1)

Published: March 11, 2025

Cognitive impairment and depressive symptoms are prevalent closely interrelated mental health issues in the elderly. Traditional methods for identifying this population often lack effectiveness. Machine learning provides a promising alternative developing predictive models that can facilitate early identification intervention. This study utilized data from 945 participants aged 60 years older with cognitive impairment, sourced National Health Nutrition Examination Surveys (2011–2014). Depressive were assessed using Patient Questionnaire-9. Lasso regression was applied feature selection, ensuring consistency across models. Several machine models, including XGBoost, Logistic Regression, Random Forest, SVM, trained evaluated. Model performance accuracy, precision, recall, F1 score, AUC. The incidence of adults 14.07%. Key predictors identified by lasso included general health, memory difficulties, age, among others. Notably, emerged as novel significant predictor population, underscoring interplay between physical health. XGBoost best model comprehensively comparing discrimination, calibration, clinical utility. particularly effectively predict cognitively impaired adults. findings highlight importance physical, cognitive, social factors risk. These have potential to assist screening intervention, improving patient outcomes. Future research should explore ways enhance generalizability, use clinically diagnosed selection approaches.

Language: Английский

AI Readiness and Trust in Government

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 58

Published: March 20, 2025

Artificial intelligence has transformed the way of thinking, human relationships, and organizational functions in developed developing countries. The Global South commenced far-reaching efforts toward streamlining AI readiness government by ensuring data protection, cybersecurity, regulation quality, ethical principles, accountability. In that context, chapter explores level Bangladesh India, especially cyber security, It further exemplifies how indicators affect trust India. also comprehensively analyzes influence institutional two countries' governments. Finally, will reveal India have addressed dialect between traditional virtual atmospheric view context artificial intelligence.

Language: Английский

Nursing Students' Perspectives on Integrating Artificial Intelligence Into Clinical Practice and Training: A Qualitative Descriptive Study

Health Science Reports, Journal Year: 2025, Volume and Issue: 8(4)

Published: April 1, 2025

ABSTRACT Background The integration of artificial intelligence (AI) into healthcare has introduced transformative tools to enhance clinical decision‐making and streamline workflows. In nursing, a profession characterized by human‐centric care, AI adoption offers both significant opportunities notable challenges. However, the perspectives nursing students, future professionals, on integrating practice education remain underexplored. Aim This study aimed explore students' perceptions incorporating their training professional practice, with focus identifying benefits, challenges, potential areas for improvement. Methods A qualitative descriptive design explored experiences attitudes 25 students from five colleges in Dhaka, Bangladesh. Participants were purposively sampled ensure diverse educational backgrounds. Semi‐structured interviews Bangla, lasting 40–50 min, audio‐recorded, transcribed, translated English. Data collected May 8, 2024 August 10, 2024. analyzed using thematic analysis identify patterns themes. Credibility was ensured through member checking, dependability via an audit trail, confirmability peer debriefing. visualization used map relationships effectively. Results Thematic revealed four major themes: (1) education, (2) ethical concerns, (3) preparedness AI‐driven (4) AI's impact practice. expressed optimism about improve accuracy efficiency apprehension readiness use effectively Conclusion findings underscore need comprehensive curriculum reforms that incorporate training, address emphasize role as supportive tool rather than replacement human expertise. These insights provide roadmap while preserving compassionate core

Language: Английский