ROLE OF CROSS SECTIONAL IMAGING IN SENSORINEURAL HEARING LOSS
Bibliographic record
Abstract
Purpose: Aims and objective of the study is to determine the incidence of structural cochlear anomalies in Sensorineural hearing loss and to evaluate them using HRCT and MRI Scan of temporal bone to asses feasibility of cochlear implantation. The study was carried out in the department of radiodiagnosis over a period of 16 mont Method: hs. The study included 114 patients of moderate to profound SNHL to evaluate further using HRCT and MRI Scan of temporal bone. Out of t Results: otal 114 pts in our study 75 pts had normal CT/MRI of temporal bone with no structural abnormalities detected and 39 number of patients had structural malformations which were feasible for cochlear implantation. Small percentage of patients (11%) with common cavity and absent cochlear nerve were not feasible for cochlear implantation. HRCT and MR imaging play an important role in evaluation of congenital heari Conclusion: ng loss by providing crucial information about the inner ear, vestibulocochlear nerve, and brain. Both modalities precisely and accurately delineate the inner ear anatomy and malformations preoperatively in cochlear implant patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".