Summary

Dear Colleagues,

The rapid advancement of Artificial Intelligence (AI) in healthcare is transforming the way medical data is analyzed, diagnoses are made, and treatments are personalized. This Topical Collection on AI in Medicine aims to bring together cutting-edge research, methodologies, and applications that leverage AI and Data Science to address key challenges in healthcare. Potential contributions include the development of intelligent diagnostic tools, predictive models for patient outcomes, personalized treatment recommendations, and the integration of heterogeneous medical datasets for improved clinical decision-making.

By focusing on AI in the medical domain, this collection encourages submissions that explore both theoretical innovations and practical implementations. Topics of interest include machine learning algorithms for medical imaging, natural language processing of electronic health records, predictive analytics in epidemiology, AI-driven drug discovery, and ethical considerations in deploying AI in clinical settings.

The goal of this collection is to provide a comprehensive overview of how AI and data-driven approaches can enhance patient care, optimize healthcare workflows, and foster innovation in medical research. We invite authors to submit original research, review articles, and case studies that demonstrate the potential and impact of AI technologies in medicine. This collection will serve as a guide for researchers, practitioners, and policy-makers interested in the intersection of AI, Data Science, and healthcare.

Dr. Otmane Azeroual
Dr. Robert Friedman
Collection Editors

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Editors
Otmane Azeroual

Institution: German Centre for Higher Education Research and Science Studies (DZHW), University of Hagen, Berlin, Germany

Interests: artificial intelligence; machine learning; data science & engineering; big data; business intelligence & data warehousing; data quality management; data integration and heterogeneous information systems

Bob Friedman

Institution: Retired from Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA

Interests: neuroinformatics; cognitive science; neuroscience; bioinformatics

Entry
Topic Review Peer Reviewed
Silsesquioxane-Based and Hydroxyapatite-Containing Hybrid Biomaterials for Bone Regeneration: Evidence, Limitations, and Future Directions
The repair of critical bone defects remains a substantial clinical challenge. A regenerative material must support osteogenesis, provide appropriate mechanical function, and degrade at a rate compatible with tissue formation. Hydroxyapatite (HA) is osteoconductive and chemically similar to bone mineral, but its brittleness and slow resorption limit its use as a stand-alone load-bearing material. Silsesquioxanes, particularly polyhedral oligomeric silsesquioxanes (POSS), provide molecularly defined silicon–oxygen frameworks with modifiable organic substituents. These can be incorporated as fillers or covalent network components. This review critically evaluates silsesquioxane-based biomaterials for bone regeneration. It distinguishes direct evidence from HA-containing systems from mechanistic analogues. These analogues include silicate-substituted HA, bioactive glass, dental POSS composites, and related polymer–POSS materials. Sol–gel processing, in situ mineralisation, particle incorporation, surface grafting, and network formation are assessed in relation to interfacial bonding, apatite nucleation, mechanical behaviour, and degradation. Current evidence indicates that reinforcement depends on cage functionality, dispersion, loading, matrix chemistry, and interfacial integration. Direct evidence that implanted HA–POSS systems release orthosilicic acid at biologically active concentrations remains unavailable. Cross-system comparisons further show that reported mechanical values cannot be ranked without accounting for physical form, porosity, test mode, and environmental conditions. The principal translational barriers are (i) the scarcity of load-bearing in vivo studies, (ii) uncertain degradation-product fate, and (iii) sterilisation sensitivity in some POSS-modified polymers. Further barriers are (iv) limited manufacturing standardisation and (v) the absence of clinically validated HA–POSS implants. The most defensible rationale for these hybrids is therefore their capacity for multifunctional interfacial design rather than universal mechanical superiority. 
  • 25
  • 04 Nov 2026

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