College of Dentistry
Anita Gohel Research Group
Led by Anita Gohel · Oral and Maxillofacial Diagnostic Sciences
What we study
The Gohel Lab studies advanced 3D imaging, jaw lesions, and pathology, using AI to improve diagnostic models and evaluate AI systems in student training. They also research early detection of salivary gland changes in Sjögren’s disease and muscle issues in TMJ disorders.
What working here is like
- Clinical
- Computational
- Projects
- 4
- Papers
- 5
Current projects
AI training dataset for 2D/3D imaging diagnosis
Creating a dataset to improve AI models for detecting normal anatomy and jaw lesions.
MRONJ-induced osteonecrosis detection
Establishing temporal radiographic features to detect MRONJ-induced osteonecrosis.
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Ultrasound imaging in Sjögren’s disease
Using ultrasound to detect early salivary gland changes in Sjögren’s disease.
Muscles of mastication in TMJ disorders
Uses imaging to evaluate how the chewing muscles change in people with temporomandibular joint (TMJ) disorders.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- Perceptions of dental students on the integration of artificial intelligence in radiology clinical education
2026 · Frontiers in Dental Medicine
Asks dental students about using AI in radiology training and their experiences.
- AI vs. Dental Students: A Comparison of Periapical Radiolucency Detection in Radiographs
2026 · Journal of Dental Education
Compares AI and dental students in detecting bone changes in dental X-rays.
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- Performance evaluation of AI-based caries detection technology and its educational training module: a dual-phase investigation
2026 · Frontiers in Dental Medicine
Evaluates an AI system for detecting tooth decay and its training module for dental students.
- Incidental detection of sellar spine on a CBCT volume: clinical and radiographic considerations
2026 · Oral Surgery Oral Medicine Oral Pathology and Oral Radiology
Describes a rare bone growth in the pituitary area found by accident during dental imaging.
- Two-dimensional vs three-dimensional facial visualization: effects on perceived attractiveness, treatment need, and modality selection across sagittal and vertical facial patterns
2026 · Digital and Aligner Orthodontics
Tests how 2D vs. 3D facial images affect perceived attractiveness and treatment choices.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Anita Gohel hasn't set up this page yet. Their UF Scholars profile lists their publications.