Role of Artificial Intelligence in Oral Cancer
Oral malignancy, notably oral squamous cell carcinoma (OSCC), stands as a formidable global health issue, characterized by disparate prevalence among demographics and geographic regions. Traditional diagnostic modalities, reliant on biopsy and histopathological methods, they all often exhibit constr...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
|
| Series: | Advances in Public Health |
| Online Access: | http://dx.doi.org/10.1155/adph/3664408 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841555817018425344 |
|---|---|
| author | Vidhya Rekha Umapathy Prabhu Manickam Natarajan Bhuminathan Swamikannu Sabarinathan Jaganathan Suba Rajinikanth Vijayalakshmi Periyasamy |
| author_facet | Vidhya Rekha Umapathy Prabhu Manickam Natarajan Bhuminathan Swamikannu Sabarinathan Jaganathan Suba Rajinikanth Vijayalakshmi Periyasamy |
| author_sort | Vidhya Rekha Umapathy |
| collection | DOAJ |
| description | Oral malignancy, notably oral squamous cell carcinoma (OSCC), stands as a formidable global health issue, characterized by disparate prevalence among demographics and geographic regions. Traditional diagnostic modalities, reliant on biopsy and histopathological methods, they all often exhibit constraints in expeditiousness and subjectivity, thus an alternative methodologies are needed for fostering early detection and personalized therapeutic strategies. Artificial intelligence (AI) emerges as a forefront avenue in oral cancer (OC) therapeutics, engaged in providing solutions for diagnostic augmentation, treatment optimization, and prognostic delineation. Machine learning paradigms, encompassing supervised and unsupervised learning, afford meticulous classification and pattern identification from multifarious clinical and histopathological datasets. Deep learning architectures, exemplified by convolutional neural networks (CNNs), automatize lesion detection, and characterization from medical imagery, thereby expediting diagnostic efficacy. Predictive analytics methodologies combine multifaceted patient data to access risk and prognosticate disease trajectory, thereby facilitating bespoke treatment schema. Expert systems harness medical knowledge and patient-centric intelligence to furnish decision support for clinicians in treatment modality selection and disease monitoring. Robotic and automated systems contribute to surgical precision and procedural streamlining, ultimately fostering enhanced patient outcomes. Despite these advancements, challenges remain persists necessitating continued interdisciplinary collaboration and research efforts. This review explores about burgeoning role of AI in OC therapeutics, elucidating extant applications, challenges, and future trajectories for research and clinical adoption in oral oncology. |
| format | Article |
| id | doaj-art-353456d392fd4752a1bae22cfe2e8131 |
| institution | Kabale University |
| issn | 2314-7784 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Public Health |
| spelling | doaj-art-353456d392fd4752a1bae22cfe2e81312025-01-08T00:00:06ZengWileyAdvances in Public Health2314-77842024-01-01202410.1155/adph/3664408Role of Artificial Intelligence in Oral CancerVidhya Rekha Umapathy0Prabhu Manickam Natarajan1Bhuminathan Swamikannu2Sabarinathan Jaganathan3Suba Rajinikanth4Vijayalakshmi Periyasamy5Department of Public Health DentistryDepartment of Clinical SciencesDepartment of ProsthodonticsDepartment of Orthodontics and Dentofacial OrthopedicsDepartment of PaediatricsPG and Research Department of Biotechnology and BioinformaticsOral malignancy, notably oral squamous cell carcinoma (OSCC), stands as a formidable global health issue, characterized by disparate prevalence among demographics and geographic regions. Traditional diagnostic modalities, reliant on biopsy and histopathological methods, they all often exhibit constraints in expeditiousness and subjectivity, thus an alternative methodologies are needed for fostering early detection and personalized therapeutic strategies. Artificial intelligence (AI) emerges as a forefront avenue in oral cancer (OC) therapeutics, engaged in providing solutions for diagnostic augmentation, treatment optimization, and prognostic delineation. Machine learning paradigms, encompassing supervised and unsupervised learning, afford meticulous classification and pattern identification from multifarious clinical and histopathological datasets. Deep learning architectures, exemplified by convolutional neural networks (CNNs), automatize lesion detection, and characterization from medical imagery, thereby expediting diagnostic efficacy. Predictive analytics methodologies combine multifaceted patient data to access risk and prognosticate disease trajectory, thereby facilitating bespoke treatment schema. Expert systems harness medical knowledge and patient-centric intelligence to furnish decision support for clinicians in treatment modality selection and disease monitoring. Robotic and automated systems contribute to surgical precision and procedural streamlining, ultimately fostering enhanced patient outcomes. Despite these advancements, challenges remain persists necessitating continued interdisciplinary collaboration and research efforts. This review explores about burgeoning role of AI in OC therapeutics, elucidating extant applications, challenges, and future trajectories for research and clinical adoption in oral oncology.http://dx.doi.org/10.1155/adph/3664408 |
| spellingShingle | Vidhya Rekha Umapathy Prabhu Manickam Natarajan Bhuminathan Swamikannu Sabarinathan Jaganathan Suba Rajinikanth Vijayalakshmi Periyasamy Role of Artificial Intelligence in Oral Cancer Advances in Public Health |
| title | Role of Artificial Intelligence in Oral Cancer |
| title_full | Role of Artificial Intelligence in Oral Cancer |
| title_fullStr | Role of Artificial Intelligence in Oral Cancer |
| title_full_unstemmed | Role of Artificial Intelligence in Oral Cancer |
| title_short | Role of Artificial Intelligence in Oral Cancer |
| title_sort | role of artificial intelligence in oral cancer |
| url | http://dx.doi.org/10.1155/adph/3664408 |
| work_keys_str_mv | AT vidhyarekhaumapathy roleofartificialintelligenceinoralcancer AT prabhumanickamnatarajan roleofartificialintelligenceinoralcancer AT bhuminathanswamikannu roleofartificialintelligenceinoralcancer AT sabarinathanjaganathan roleofartificialintelligenceinoralcancer AT subarajinikanth roleofartificialintelligenceinoralcancer AT vijayalakshmiperiyasamy roleofartificialintelligenceinoralcancer |