Clinical Progress of Diabetic Foot

A Special Issue of Journal of Personalized Medicine (ISSN 2075-4426) belonging to the section "Personalized Therapy in Clinical Medicine".

Deadline for manuscript submissions: 31 May 2027 | Viewed by 1198

Editors


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Guest Editor
Diabetes Unit, and Diabetes Foot Unit, Azienda Unità Sanitaria USL CENTRO Toscana (Area Pistoiese), San Jacopo Hospital, Via Ciliegiole, 51100 Pistoia, Italy
Interests: diabetes; diabetic foot; metabolic syndrome; obesity; physical activity; sport; biomechanics; posture; telemonitoring; data analysis
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Diabetes Unit and Diabetes Foot Unit, General Hospital of Pistoia, 51100 Pistoia, Italy
Interests: diabetes; diabetic foot; obesity; metabolic syndrome; epidemiology; physical activity; sport; telemedicine; data analysis
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Information Engineering, University of Florence, 50139 Florence, Italy
Interests: classification; algorithms; neural networks; segmentation; tracking; signal processing; image processing; image analysis; pattern recognition; computer vision
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Diabetes and Metabolic Diseases Unit, San Giovanni di Dio Hospital, 50143 Florence, Italy
Interests: biomaterials and ulcer healing; telemonitoring and imaging; AI driven personalized offloading devices; care pathways and clinical diagnostic therapeutic paths (PDTA); therapeutic education

Special Issue Information

Dear Colleagues,

Diabetic foot complications remain one of the most significant challenges in diabetes care, with high rates of morbidity and amputation. This Special Issue explores the latest clinical advances in the management of diabetic foot disease, emphasizing the role of personalized medicine.

Advances in biomarker identification and individualized treatment strategies are transforming clinical approaches, enabling tailored interventions that address the unique needs of each patient. However, integrating personalized treatment strategies into clinical practice remains an emerging challenge. This issue aims to provide a comprehensive overview of how personalized care is improving the prognosis and quality of life for individuals with diabetic foot complications.

We invite contributions related to original studies and literature reviews that discuss novel diagnostic tools, cutting-edge therapies, and the integration of personalized medicine in preventing, managing, and treating diabetic foot ulcers and infections.

Dr. Piergiorgio Francia
Dr. Roberto Anichini
Dr. Leonardo Bocchi
Dr. Alessandra De Bellis
Guest Editors

Manuscript Submission Information

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Keywords

  • diabetic foot
  • personalized medicine
  • advanced therapies
  • clinical management
  • biomarkers
  • diabetes complications
  • risk assessment
  • preventive care
  • artificial intelligence
  • data science

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Published Papers (1 paper)

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Review

19 pages, 376 KB  
Review
Clinical Significance of Non-Invasive Skin Autofluorescence Measurement and AI Applications in Patients with Diabetic Foot Ulcers: A Scoping Review
by Cosimo Aliani, Piergiorgio Francia, Cosimo Nardi, Alessandra De Bellis, Roberto Anichini and Leonardo Bocchi
J. Pers. Med. 2026, 16(6), 285; https://doi.org/10.3390/jpm16060285 - 26 May 2026
Viewed by 703
Abstract
Emerging optical technologies may offer new opportunities for the non-invasive assessment of diabetic foot ulcers (DFUs), but the role of artificial intelligence (AI)-assisted autofluorescence-based approaches remains unclear. This scoping review aimed to map and summarise the published evidence on AI-assisted analysis of autofluorescence/fluorescence-based [...] Read more.
Emerging optical technologies may offer new opportunities for the non-invasive assessment of diabetic foot ulcers (DFUs), but the role of artificial intelligence (AI)-assisted autofluorescence-based approaches remains unclear. This scoping review aimed to map and summarise the published evidence on AI-assisted analysis of autofluorescence/fluorescence-based signals for DFU assessment and management. We searched Scopus, Web of Science, Embase, PubMed, CINAHL, Google Scholar, and the SPIE Digital Library, and also considered conference proceedings. We included English-language studies published between 2010 and October 2025. Of 197 records identified through database searching, 22 full-text articles were assessed for eligibility, and 5 studies met the inclusion criteria. Four studies focused on infection-related applications, specifically bacterial burden detection and Gram-type classification, whereas one study investigated tissue oxygenation estimation using a related optical imaging approach. All included studies were published between 2022 and 2025, were conducted in India, and four of the five evaluated the same device family or related variants. Overall, the evidence base was limited, geographically restricted, and technologically narrow. In addition, reporting of participant characteristics and AI methodology was often incomplete, with several studies relying on embedded proprietary or insufficiently described algorithmic components. Taken together, the available literature supports early proof-of-feasibility in restricted and largely device-specific evaluation settings rather than robust evidence of broad clinical validity, implementation readiness, or routine-care utility. Larger, more diverse, and independently validated studies with standardised acquisition procedures and more transparent AI reporting are needed before these approaches can be meaningfully evaluated for routine DFU care. Full article
(This article belongs to the Special Issue Clinical Progress of Diabetic Foot)
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