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Assessing the Reliability of the ORADIII (Oral Radiology Artificial Intelligence Diagnostic - Version 3) Software
Kavya Shankar Muttanahally1, Juan Gonzalez2, Gabriel P Crocker2
1Oral and Maxillofacial Radiology, University of Nebraska Medical Center, Lincoln, USA.
Artificial intelligence software ORADIII shows potential for diagnosing jaw lesions but is less accurate than oral radiologists. Clinical expertise remains crucial for accurate dental diagnoses.
Area of Science:
- Dentistry
- Radiology
- Artificial Intelligence
Background:
- Accurate interpretation of radiographic images is vital for dentists' diagnoses and treatment planning.
- The diagnostic reliability of general dentists for jaw lesions can be uncertain.
- Cone-beam computed tomography (CBCT) is a key imaging modality in modern dentistry.
Purpose of the Study:
- To evaluate the diagnostic efficacy of ORADIII (Oral Radiology Artificial Intelligence Diagnostic - Version 3) software in interpreting jaw lesions from CBCT scans.
- To compare the diagnostic performance of ORADIII with that of an oral and maxillofacial radiologist.
- To assess the accuracy of AI-driven differential diagnoses against expert clinical judgment and biopsy results.
Main Methods:
- 100 CBCT scans of patients with jaw lesions were analyzed (85 with biopsy confirmation).
- ORADIII's top three differential diagnoses were recorded and compared to a radiologist's diagnoses.
- The radiologist utilized clinical information and 3D-rendering software for their diagnoses.
Main Results:
- The oral radiologist achieved 68% accuracy compared to biopsy results.
- ORADIII demonstrated 21% accuracy in comparison to the oral radiologist's diagnoses.
- ORADIII correctly identified 5 out of 6 dentigerous cysts, but overall accuracy was significantly lower than the radiologist's (p<0.05).
Conclusions:
- ORADIII shows promise as a supplementary tool for dentists but is not a substitute for expert clinical judgment.
- Further research is needed to enhance AI algorithms with more clinical data and machine learning for improved diagnostic accuracy.
- The study highlights the synergistic role of technology and clinical expertise in achieving accurate dental diagnoses.
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