Oral Cancer and Artificial Intelligence

Transforming Diagnosis, Treatment, and Research
Erscheinungsjahr 2026
ISBN: 978-0-443-34423-7
Verlag: Elsevier Science

Buch, Englisch, 448 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

Oral Cancer and Artificial Intelligence: Transforming Diagnosis, Treatment, and Research explores the intersection of artificial intelligence (AI) and oral cancer care. Sections detail how AI technologies are revolutionizing and evolving diagnosis, treatment, and management, offering new hope and improved outcomes for patients. The book is structured into ten well-defined sections, each addressing a critical aspect of oral cancer care enhanced by AI. It features contributions from leading experts in the fields of AI, oral cancer research, biomedical engineering, and clinical practice from prestigious, worldwide institutions who share valuable insights and their experiences in applying AI to transform oral cancer care.

This book is an essential resource for researchers, clinicians, healthcare professionals, and students interested in the transformative potential of AI in oral cancer care. It offers a blend of theoretical knowledge, practical applications, and future directions, making it a comprehensive guide to understanding and leveraging AI to improve outcomes in oral cancer management.

Autoren/Hrsg.

Dash, Sujata

Pani, Subhendu Kumar

Chakraborty, Somenath

Aladelusi, Timothy

Jayasinghe, Ruwan Duminda

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften

Inhaltsverzeichnis

SECTION I: Introduction to oral cancer and AI

1 Oral cancer overview
2 Role of artificial intelligence in healthcare

SECTION II: AI in early detection and screening

3 AI-enhanced screening tools: Innovations and challenges in oral cancer detection
4 Image analysis and pattern recognition

SECTION III: AI in diagnosis

5 AI-driven diagnostic systems
6 Natural language processing for histopathology

SECTION IV: AI in treatment planning and decision support

7 Artificial Intelligence in surgical planning
8 Precision radiotherapy in the era of artificial intelligence and big data analytics
9 Chemotherapy and artifical intelligence-based treatment protocols

SECTION V: AI in prognosis and outcome prediction

10 Artificial intelligence in the prognosis of oral cancer
11 Survival analysis and risk stratification

SECTION VI: AI in rehabilitation and patient support

12 Post-treatment AI applications
13 Artificial intelligence in quality of life (QOL) assessment for oral cancer patients

SECTION VII: Data management and AI integration

14 Big data and AI in oral cancer
15 Ethical and legal consideration associated with AI use

SECTION VIII: Emerging AI technologies and future directions

16 Innovations in oral cancer management enabled by artificial intelligence (AI)
17 Future trends in AI and oral cancer

SECTION IX: Case studies and practical applications

18 AI in clinical practices
19 Practical implementation of AI technologies in oral cancer

SECTION X: Conclusion

20 Summary and outlook

Über Autor(innen)

Pani, Subhendu Kumar
Subhendu Kumar Pani received his PhD from Utkal University, Odisha, India, in 2013. He currently serves as Principal of Krupajal Engineering College, Bhubaneswar, India, and has over 17 years of teaching and research experience. A prolific author, he serves as Series Editor for CRC Press’ Advances in Computational Collective Intelligence, Apple Academic Press’ AAP Advances in Artificial Intelligence & Robotics, and Wiley-Scrivener’s Intelligent Data Analytics for Terror Threat Prediction, and is actively involved as an associate editor, editorial board member, and reviewer for several international journals. He also contributes to national and international conference communities. His research interests include data mining, big data analytics, web data analytics, fuzzy decision-making, and computational intelligence. He is a Fellow of SSARS (Canada) and a Life Member of several professional bodies, including IE, ISTE, ISCA, OBA, OMS, SMIACSIT, SMUACEE, and CSI. He has received multiple research awards in recognition of his contributions.

Dash, Sujata
Sujata Dash is a Professor of Information Technology at Nagaland University, India, and an IEEE Senior Member, with over three decades of academic and research experience. She holds a PhD in Computational Modeling and has also completed postdoctoral research at the University of Manitoba, Canada, where she later served as a Visiting Professor. Her research spans machine learning, deep learning, artificial intelligence, bioinformatics, natural language processing, and IoT, with applications across healthcare, data science, and smart systems. Dr. Dash has an extensive publication record with leading publishers including Elsevier, Springer, Wiley, and CRC Press, and serves on the editorial boards of several international journals. She has delivered keynote lectures and chaired sessions at numerous international conferences and has received several awards, including the Global Distinguished Award (IEEE IAS, 2023), Outstanding Scientist Award, and Best Researcher Award.

Chakraborty, Somenath
Dr. Somenath Chakraborty is an Assistant Professor at The West Virginia University Institute of Technology in Beckley, West Virginia, USA. With 11 years of experience in various academic roles, including Lecturer, Assistant Professor, and Principal at multiple government ITIs, he has developed strong research expertise in artificial intelligence, medical image and data processing, machine learning, pattern recognition, and digital image processing. He has authored numerous research journals, conference papers, and book chapters. As an IEEE Senior Member, he is involved with the IEEE Computer Society, IEEE Computational Intelligence Society, and other professional organizations. Additionally, he serves as a reviewer for various IEEE and Springer journals, and is an editor for several publications. Somenath has held leadership roles in the Graduate Student Association for Arts and Sciences at The University of Southern Mississippi. His research interests include machine learning, data science, computer vision, and blockchain technology.

Aladelusi, Timothy
Dr Timothy Aladelusi obtained the Bachelor of dental Surgery from the University of Ibadan in 2003 and proceeded to obtained his Masters degree in Anatomy from the same institution in 2008. He had his residency training in Oral and Maxillofacial Surgeon of the West African College of Surgeon at the University College Hospital, Ibadan from June 2006 to Oct 2012. He was awarded the Fellowship of the AOCMF in Craniomaxillofacial Trauma done the Hannover Medical School Germany in 2014. He also received the International association of Oral and Maxillofacial Surgeons Fellowship in Maxillofacial oncology and reconstruction which he did under the tutelage of Prof Zhang Chen Ping at the Ninth People’s Hospital, Shanghai, PRC in 2017/2018. His research interest is maxillofacial trauma, dento-alveolar surgery and maxillofacial oncology and reconstruction. He has over 40 publications in peer reviewed journals.

Jayasinghe, Ruwan Duminda
Prof Ruwan Jayasinghe is a health specialist with over 20 years’ experience in teaching, clinical dental practice, scholarly research, and leadership. Prof Jayasinghe has academic/professional qualifications in Dentistry, Oral and Maxillofacial Surgery, Oral Medicine, and Oral Radiology. He has collaborated with multiple national and international institutions/organizations of learning/teaching and research. Prof Jayasinghe has over 150 peer reviewed publications, with several citations. He has received various research grants. He has been recognized for his teaching and research work with multiple wards. Prof Jayasinghe has contributed to the professional associations by holding high ranking positions. He is an editorial board member to multiple journals and is also a referee to 40 prestigious journals.