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Special Issues
Personalized Prevention, Diagnosis and Treatment of Skin Disorders
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Personalized Prevention, Diagnosis and Treatment of Skin Disorders

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 694

Special Issue Editors

Prof. Dr. Carmen Cantisani

E-Mail Website
Guest Editor
Dermatology Clinic, Department of Internal, Anesthesiologic and Cardiovascular Sciences, “Sapienza” University of Rome, 00161 Rome, Italy
Interests: non-invasive diagnostic imaging in dermatology; skin cancer; non-surgical treatment of non-melanoma skin cancer
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Beata Bergler-Czop

E-Mail Website
Guest Editor
Department of Dermatology, Medical University of Silesia, Francuska Str. 20-24, 40-027 Katowice, Poland
Interests: acne; psoriasis; systemic sclerosis; scleroderma spectrum disorders
Prof. Dr. Emanuele Cigna

E-Mail Website
Guest Editor
Plastic Surgery and Microsurgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56121 Pisa, Italy
Interests: microsurgery; breast reconstruction; head and neck; lymphatics; sarcoma; lower limb reconstruction; melanoma; autologous breast reconstruction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Skin disorders affect millions of individuals globally, presenting a significant challenge in dermatological therapy. They are often complex diseases with a polygenic background, immune mechanisms, and environmental triggers. Despite extensive public awareness, intervention, and screening programs, the incidence of skin cancers especially continues to rise rapidly. These conditions require effective and innovative diagnostic techniques and therapeutic approaches for their management and treatment.

The aim of this Special Issue is to gather articles that present recent advancements in research involving the mechanisms that underlie the development of skin disorders, new technologies, as well as clinical research for personalized treatment focusing on surgery and prevention.  Both clinical and basic science studies are to be considered. We warmly invite researchers to submit reviews, original research articles, communications, and systematic reviews in the field.

Prof. Dr. Carmen Cantisani
Prof. Dr. Beata Bergler-Czop
Prof. Dr. Emanuele Cigna
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. Journal of Personalized Medicine 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

  • skin disorders
  • skin diseases
  • dermatology
  • dermoscopy
  • reflectance confocal microscopy
  • optical coherence tomography—LC-OCT
  • non-melanoma skin cancer
  • melanoma
  • photodynamic therapy
  • raynaud phenomenon
  • scleroderma

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Published Papers (1 paper)

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13 pages, 468 KiB  
Systematic Review
Artificial Intelligence in the Assessment and Grading of Acne Vulgaris: A Systematic Review
by Daniele Omar Traini, Gerardo Palmisano, Cristina Guerriero and Ketty Peris
J. Pers. Med. 2025, 15(6), 238; https://doi.org/10.3390/jpm15060238 - 6 Jun 2025
Viewed by 433
Abstract
Acne vulgaris is a common dermatological condition, particularly affecting adolescents during critical developmental stages, which may have lasting psychosocial impacts. Traditional assessments, including global severity grading and lesion counting, are limited by subjectivity and time constraints. Background/Objectives: This review aims to systematically [...] Read more.
Acne vulgaris is a common dermatological condition, particularly affecting adolescents during critical developmental stages, which may have lasting psychosocial impacts. Traditional assessments, including global severity grading and lesion counting, are limited by subjectivity and time constraints. Background/Objectives: This review aims to systematically assess the recent advancements in artificial intelligence (AI) applications for acne diagnosis, lesion segmentation/counting, and severity grading, highlighting the potential of AI-driven methods to improve objectivity, reproducibility, and clinical efficiency. Methods: A comprehensive literature search was conducted across PubMed, Scopus, arXiv, Embase, and Web of Science for studies published between 1 January 2017 and 1 March 2025. The search strategy incorporated terms related to “acne” and various AI methodologies (e.g., “neural network”, “deep learning”, “convolutional neural network”). Two independent reviewers screened 345 articles, with 29 studies ultimately meeting inclusion criteria. Data were extracted on study design, dataset characteristics (including internal and publicly available resources such as ACNE04 and AcneSCU), AI architectures (predominantly CNN-based models), and performance metrics. Results: While AI-driven models demonstrated promising accuracy, as high as 97.6% in controlled settings, the limited availability of large public datasets, the predominance of data from specific ethnic groups, and the lack of extensive external validation underscore critical barriers to clinical implementation. Conclusions: The findings indicate that although AI has the potential to standardize acne assessments, reduce observer variability, and enable self-monitoring via mobile platforms, significant challenges remain in achieving robust, real-world applicability. Future research should prioritize the development of large, diverse, and publicly accessible datasets and undertake prospective clinical validations to ensure equitable and effective dermatological care. Full article
(This article belongs to the Special Issue Personalized Prevention, Diagnosis and Treatment of Skin Disorders)
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