Machine Learning for Advanced Healthcare: Bridging Innovation and Clinical Implementation
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms and Mathematical Models for Computer-Assisted Diagnostic Systems".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 73
Special Issue Editors
Interests: life and medical sciences; machine learning; machine learning for biomedical data interpretation; REM sleep behaviour disorder; sleep disorders
Interests: biomedical signal processing; acquisition, analyses and interpretation of biomedical signals
Interests: surgical robotics; telemedicine; IoT devices; human-robot interaction; soft and stretchable robotics; industrial robotics; sensors and actuators; energy harvesting
Special Issue Information
Dear Colleagues,
Digital transformation is revolutionizing healthcare, leading to a more efficient management of health-related information, diagnostics, and patient care. Machine learning (ML) plays a crucial role in this evolution, offering advanced solutions for early disease detection, continuous patient monitoring, and personalized treatment. However, the efficacious translation of ML from proof-of-concept studies to real-world clinical applications not only requires high predictive accuracy, but also transparent, reliable, and interpretable decision-making processes.
The growing availability of multimodal health data—from physiological signals, wearable sensors, medical imaging, and remote or real-time patient monitoring—offers the opportunity to develop explainable and reliable ML frameworks. Hence, these strategies could significantly support clinical decision-making, particularly benefiting individuals with chronic conditions, ageing populations, and those with limited healthcare access.
This Special Issue aims to bridge the gap between ML advancements and their actual implementation in healthcare; specifically, it focuses on the development and application of interpretable ML frameworks in real-world clinical settings.
For this Special Issue, we invite submissions presenting explainable AI strategies, multi-source data integration, and interpretable solutions to support early diagnosis, monitoring, and predictive modelling of disease progression. Studies addressing challenges in data integration, model interpretability, physician–AI interaction, and privacy-preserving approaches are highly encouraged.
Potential topics include, but are not limited to:
- ML models to support early diagnosis and disease progression monitoring;
- Wearable technologies and sensor-based data analysis;
- Interpretable methods for sleep, motor, and cognitive assessments;
- Multimodal data integration and fusion;
- Explainable AI for clinical decision-making;
- ML for remote monitoring and telemedicine;
- Predictive models for personalized treatment;
- Federated learning and privacy-preserving ML;
- Big data in healthcare and e-Health;
- Generalizability, interpretability, and visualization in healthcare.
Dr. Irene Rechichi
Dr. Silvia Seoni
Dr. Sujit Kumar Sahu
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. Algorithms 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 1600 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
- interpretable machine learning
- wearable technology and remote health monitoring
- multimodal health data integration
- sensor data analysis
- health information systems
- explainable AI (XAI) in healthcare
- trustworthy AI for clinical practice
- biomedical signal processing
- e-Health, telemedicine, and digital health
- human motion analysis and rehabilitation technologies
- AI for sleep and neurological disorders
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