Advanced Machine Learning for Disease Prediction and Prevention
A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Medical Research".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 572
Special Issue Editors
Interests: healthcare machine learning; computational analysis of medical images; intelligent diagnostic imaging systems; vision-based healthcare solutions; analytics of healthcare and clinical datasets; fusion of multi-modal imaging data; natural language processing; information retrieval; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; deep learning; medical imaging; image processing; biomedical informatics; healthcare data science
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The emergence of large-scale, complex health datasets and advanced experimental platforms, combined with powerful computational tools, is transforming disease prediction and prevention. Advanced machine learning (ML) methods have become essential for analyzing these data to uncover subtle patterns, enhance risk assessment, and enable timely interventions across diverse diseases.
This Special Issue focuses on innovative research applying advanced ML techniques to improve disease prediction and prevention. We welcome contributions addressing key challenges such as integrating multimodal biomedical and clinical data, developing interpretable and explainable AI (XAI) models, mitigating algorithmic bias, and establishing robust validation frameworks to ensure clinical reliability.
Submissions may include novel algorithms, methodological advancements, clinical applications, comprehensive reviews, and future perspectives. Interdisciplinary work bridging bioinformatics, population health, clinical practice, and public health is especially encouraged.
Our goal is to showcase how advanced ML approaches can advance proactive healthcare by enabling earlier detection, improved risk stratification, and more effective prevention strategies. This Special Issue aims to foster collaboration and innovation across disciplines to drive impactful progress in disease prediction and prevention.
This Special Issue invites submissions addressing the following topics:
- Development and application of advanced machine learning methods for disease prediction and prevention
- Integration of multimodal biomedical and clinical data for enhanced predictive modeling
- Explainable AI (XAI) techniques for improving model transparency and interpretability in healthcare
- Strategies to mitigate algorithmic bias and ensure fairness in medical AI systems
- Robust validation methods and evaluation metrics for predictive healthcare models
- Machine learning approaches for early detection and risk stratification of various diseases
- Clinical case studies demonstrating real-world application of AI in disease prevention
- Novel algorithms and methodological advancements in computational health analytics
- Interdisciplinary research combining computational science, public health, and medical informatics
- Ethical, legal, and social implications of AI-driven disease prediction models
Dr. Jawad Khan
Dr. Dildar Hussain
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- advanced machine learning
- disease prediction
- disease prevention
- biomedical data integration
- multimodal data
- explainable AI (XAI)
- AI Interpretability
- algorithmic fairness
- bias mitigation
- predictive modeling
- healthcare analytics
- risk stratification
- early disease detection
- clinical decision support
- computational health
- public health informatics
- AI ethics in healthcare
- medical AI validation
- health data science
- personalized medicine
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