Advances in Skin Cancer Diagnosis and Management
A special issue of Cancers (ISSN 2072-6694).
Deadline for manuscript submissions: 31 March 2027 | Viewed by 81
Special Issue Editor
2. Department of Dermatology, “Elias” University Emergency Hospital, 011461 Bucharest, Romania
Interests: skin cancer; melanoma
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Skin cancers represent an important socio-economic problem at a global level, with their incidence showing a continuous, progressive increase over the last 20 years, driven by both improved diagnostic accuracy (through non-invasive or invasive methods) and increases in population addressability and life expectancy.
Recent advances in dermatological imaging, minimally invasive diagnostic technologies, digital medicine, and data-driven approaches have opened new perspectives in dermatology and dermatopathology. In parallel, developments in artificial intelligence (AI), machine learning, and medical image analysis are increasingly being explored to support clinical and paraclinical decision-making.
The Special Issue “Advances in Skin Cancer Diagnosis and Management” aims to bring together scientific contributions highlighting emerging diagnostic approaches, technological innovations, and new strategies for the clinical management of skin cancers. The scope covers the full spectrum of research, from early detection and risk stratification to treatment optimization and disease monitoring.
Original research articles, systematic reviews, and meta-analyses are encouraged, particularly those addressing topics such as:
- Novel diagnostic approaches for skin cancers;
- Clinical and dermatoscopic image analysis;
- Histopathological and digital pathology advancements;
- Artificial intelligence and machine learning applications in dermatology;
- Minimally invasive dermatological diagnostic techniques (OCT, RCM, LT-OCT, HFUS, digital dermoscopy);
- Biomarkers and predictive models for recurrence, metastasis, or disease progression;
- Advances in teledermatology and digital health in skin cancer care;
- Therapeutic innovations and clinical management strategies;
- Ethical, legal, and regulatory aspects related to emerging technologies in dermatology.
This Special Issue aims to foster interdisciplinary collaboration between dermatologists, dermatopathologists, oncologists, biomedical engineers, and data scientists, promoting innovative approaches to improve the diagnosis, management, and outcomes of patients with skin cancer.
Dr. Vlad Mihai Voiculescu
Guest Editor
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 communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
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. Cancers is an international peer-reviewed open access semimonthly 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 2900 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 cancer
- diagnosis
- treatment
- artificial intelligence
- dermatological imaging
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