AI-Driven Health and Wellbeing: Self-Monitoring, Early Detection, and Multi-Criteria Personalized Decision Support
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: 20 June 2026 | Viewed by 7
Special Issue Editor
Interests: artificial intelligence; healthcare; public health; healthy lifestyle; psychomotor competencies; education; security; MCDM
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue examines how artificial intelligence can support health by integrating self-monitoring data, self-testing insights, predictive modeling, and personalized lifestyle guidance and healthcare. As wearable devices, mobile apps, and digital self-assessment tools have become common; individuals have been increasingbly able to access physiological and behavioral information, yet turning these data streams into clear and meaningful recommendations remains a challenge.
We invite research regarding the use of AI techniques in trend analysis, risk prediction, and data analysis for self-testing and self-monitoring, as well as regarding adaptations to guidance over time. Further, we highlight how MCDM frameworks help ensure that suggestions are clear, sensitive to context, and aligned with people's priorities and everyday situations.
Reserachers in public health, computer science, behavioral science, digital health, sports and movement science, healthcare, and decision sciences are all welcome to contribute. Topics include, but are not limited to, the following:
- AI-based interpretation of self-monitoring and self-testing data;
- Predictive and early risk detection models;
- Data selection and feature engineering in personalized health systems;
- AI and MCDM decision support for lifestyle recommendations;
- Wearable and movement analytics in daily settings;
- Personalized guidance for exercise, nutrition, recovery, and stress management;
- Ethical and practical issues in implementing AI-supported wellbeing.
This Special Issue highlights technologically advanced yet human-centered approaches that enable health guidance to be adaptive, clear, and personally meaningful.
Prof. Dr. Stanislav Dadelo
Guest Editor
Manuscript Submission Information
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Keywords
- digital health analytics
- self-assessment data
- wearable sensor data
- behavioral and physiological indicators
- feature selection and data fusion
- adaptive decision-support systems
- hybrid evaluation models
- explainable modeling
- personalized lifestyle adaptation
- proactive wellness interventions
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