Clinical and Radiographic Features of Ameloblastoma: Ultimate Diagnosis and Treatment
Bibliographic record
Abstract
Objectives: The purpose of this study was to compare the clinical and radiographic features of 22 intraosseous ameloblastomas. Study design: All the data with respect to the patient’s age, sex, tumor locations, surgical treatment history, as well as radiographic findings and number of recurrence, were analyzed. Results: The patient’s age at biopsy ranged from 08 to 70 years (mean, 31.5 years), Fourteen (63.6%) of the 22 subjects were females, and eight (36.4%) were males. Nineteen (86.4%) of the 22 ameloblastomas were located in mandible and three (13.6%) were located in maxilla. Pain, swelling and purulent discharge were the most common symptoms and were experienced by eight (36.4%) patients. Radiographically, seventeen (77.3%) of the 22 tumors were multilocular. Remaining five cases were unilocular with a well-demarcated border. There was no case exhibiting the typical soap-bubble appearance. The most common histologic pattern was plexiform and had follicular type. Conclusion: Diagnosis of ameloblastoma remained in doubt after clinical and radiographic examination. A biopsy is necessary for the confirmation of diagnosis. Surgical treatment should be planned after C.T and 3D Scan. Long-term follow-up at regular intervals after surgery is also recommended. Keywords: Ameloblastoma, Diagnosis, Radiographic DOI : 10.7176/JMPB/60-02 Publication date :October 31 st 2019
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".