About this Research Topic
Oral cancer remains a serious global health issue, accounting for a significant portion of head and neck cancer cases worldwide. Despite advances in treatment, survival rates have seen limited improvement over the last few decades, primarily due to late-stage diagnosis, tumor complexity, and limited treatment response in certain patient populations. There is an urgent need for innovative diagnostic tools and personalized treatment approaches to improve early detection, therapeutic outcomes, and overall patient survival.
This Research Topic will focus on exploring the next-generation technologies that are transforming the field of oral cancer diagnosis and treatment, alongside the critical role of multidisciplinary integration in advancing clinical care. Emerging technologies such as liquid biopsy, artificial intelligence (AI), machine learning (ML), and advanced imaging techniques are showing immense potential in enabling earlier and more accurate detection of oral cancer. By integrating molecular profiling and biomarker analysis, these technologies offer new pathways to better stratify patients, predict treatment response, and monitor disease progression.
Additionally, AI-driven imaging solutions, combined with digital pathology and genomics, are paving the way for precise, real-time diagnostic methods that can be incorporated into routine clinical practice. The research contributions under this theme will explore how these technologies are being implemented and their impact on patient care. We also aim to address the challenges related to integrating these tools into diverse healthcare systems, especially in resource-limited settings.
The multidisciplinary nature of modern cancer care is essential to the success of these technological advancements. This collection will promote collaboration across disciplines, bringing together clinicians, surgeons, oncologists, radiologists, pathologists, and biomedical researchers to contribute insights on how a multidisciplinary framework can optimize patient outcomes. We welcome studies, reviews, and clinical trials that showcase the integration of surgical, radiological, and therapeutic innovations, highlighting how collective expertise and teamwork are reshaping oral cancer management.
The scope of this Research Topic includes but is not limited to:
· Next-generation diagnostic tools such as liquid biopsy, AI-based imaging, and molecular profiling.
· Innovations in biomarker discovery for early detection and monitoring of oral cancer.
· Case studies demonstrating multidisciplinary care approaches for personalized treatment.
· Integration of novel therapeutic techniques in clinical practice.
· Applications of AI, machine learning, and digital tools in oral cancer diagnosis and prognosis.
· Challenges and opportunities in implementing next-generation technologies in diverse clinical settings.
· Clinical trials and studies highlighting collaborative treatment approaches.
The overarching goal of this Research Topic is to bridge the gap between technological innovation and clinical application, fostering a deeper understanding of how advanced technologies and multidisciplinary collaboration can improve outcomes in oral cancer diagnosis and treatment. We invite researchers, clinicians, and industry experts to contribute their latest findings and innovations, further advancing the future of oral cancer care.
Conflict of Interest Declaration:
We declare that none of the Topic Editors for this collection has any conflict of interest in relation to the research or publications associated with this project.
This Research Topic will focus on exploring the next-generation technologies that are transforming the field of oral cancer diagnosis and treatment, alongside the critical role of multidisciplinary integration in advancing clinical care. Emerging technologies such as liquid biopsy, artificial intelligence (AI), machine learning (ML), and advanced imaging techniques are showing immense potential in enabling earlier and more accurate detection of oral cancer. By integrating molecular profiling and biomarker analysis, these technologies offer new pathways to better stratify patients, predict treatment response, and monitor disease progression.
Additionally, AI-driven imaging solutions, combined with digital pathology and genomics, are paving the way for precise, real-time diagnostic methods that can be incorporated into routine clinical practice. The research contributions under this theme will explore how these technologies are being implemented and their impact on patient care. We also aim to address the challenges related to integrating these tools into diverse healthcare systems, especially in resource-limited settings.
The multidisciplinary nature of modern cancer care is essential to the success of these technological advancements. This collection will promote collaboration across disciplines, bringing together clinicians, surgeons, oncologists, radiologists, pathologists, and biomedical researchers to contribute insights on how a multidisciplinary framework can optimize patient outcomes. We welcome studies, reviews, and clinical trials that showcase the integration of surgical, radiological, and therapeutic innovations, highlighting how collective expertise and teamwork are reshaping oral cancer management.
The scope of this Research Topic includes but is not limited to:
· Next-generation diagnostic tools such as liquid biopsy, AI-based imaging, and molecular profiling.
· Innovations in biomarker discovery for early detection and monitoring of oral cancer.
· Case studies demonstrating multidisciplinary care approaches for personalized treatment.
· Integration of novel therapeutic techniques in clinical practice.
· Applications of AI, machine learning, and digital tools in oral cancer diagnosis and prognosis.
· Challenges and opportunities in implementing next-generation technologies in diverse clinical settings.
· Clinical trials and studies highlighting collaborative treatment approaches.
The overarching goal of this Research Topic is to bridge the gap between technological innovation and clinical application, fostering a deeper understanding of how advanced technologies and multidisciplinary collaboration can improve outcomes in oral cancer diagnosis and treatment. We invite researchers, clinicians, and industry experts to contribute their latest findings and innovations, further advancing the future of oral cancer care.
Conflict of Interest Declaration:
We declare that none of the Topic Editors for this collection has any conflict of interest in relation to the research or publications associated with this project.
Keywords: Oral Cancer Diagnosis, Multidisciplinary Integration, Liquid Biopsy, Artificial Intelligence in Oncology, Biomarker Discovery, Machine Learning Applications.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
