Gynecological Oncology: Advanced Diagnosis and Management in 2025
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 35
Special Issue Editor
Interests: clinical oncology; gynecological oncology; gyneco-oncology surgery; HPV
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Gynecological oncology is rapidly evolving, with a growing demand for advancements in diagnosis and management strategies. The need for early detection, improved treatment options, and a better understanding of the underlying mechanisms of gynecological cancers has never been more important. This Special Issue aims to bring together leading experts, researchers, and clinicians from around the world to share their insights, innovations, and research findings related to gynecological oncology. We welcome manuscripts on the etiology, diagnosis, and treatment of female cancers from early to advanced stages, as well as research from any discipline related to this area of interest.
To ensure the highest quality of contributions, we assembled a distinguished panel of experts to serve as Guest Editors for this Special Issue. We believe that the publication of this Special Issue in Diagnostics will serve as a valuable resource for clinicians, researchers, and healthcare professionals involved in the care and management of gynecological oncology patients. It will also contribute to the overall advancement of our understanding of these complex diseases.
Topics of interest for this Special Issue include (but are not limited to) the following:
- New trends in gynecologic oncology research;
- Novel diagnostic techniques and biomarkers in gynecological cancers;
- Advances in surgical interventions and minimally invasive procedures;
- Personalized treatment approaches for gynecological malignancies;
- Multidisciplinary care and collaborative management strategies;
- Novelties in histopathological processing;
- Radiological staging of gynecologic cancer;
- Surgical staging of gynecologic cancer;
- Pre- and postoperative care;
- Standardization of surgical methods;
- Sentinel lymph node mapping;
- Role of image-guided radiation therapy;
- Neoadjuvant and adjuvant chemotherapy;
- Palliative care and quality-of-life considerations;
- Artificial intelligence, machine learning, emerging digital technologies, and their impact in gynecological oncology.
Dr. Zoard T. Krasznai
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 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. Diagnostics 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 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
- gynecology
- oncology
- endometrial cancer
- ovarian cancer
- cervical cancer
- diagnosis
- staging
- surgical methods
- standardization of surgery
- treatment
- innovation
- precision medicine
- artificial intelligence
- machine learning
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