Artificial intelligence as a predictive tool for sex determination using the maxillary sinus measurements in a CBCT
- Registration Number
- CTRI/2021/04/032922
- Lead Sponsor
- Priyadharshini
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
The CBCT images of patients who have visited the dental radiology centres in the age group of 20 â?? 70 years
1.Patients with large craniofacial asymmetries involving the maxillary sinus.
2.Patients with absence of any posterior teeth in the maxilla.
3.Patients with history of paranasal sinus surgery.
4.Patients with history of maxillofacial trauma involving the maxillary sinus.
5.Patients with history of pathological processes in the maxillary sinuses, such as chronic sinusitis or mucus retention phenomenon, odontogenic cysts.
6.CBCT images or artefacts impairing the complete visualization of the maxillary sinuses and the maxillary dental arch.
7.Scans that were not covering the entire extent of the sinus.
8.Patients who are not willing to take part in the study.
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Artificial Neural Network predicts the gender using volumetric and linear CBCT measurements of maxillary sinusTimepoint: Maxillary sinus linear and volumetric measurements are done in CBCT and data are fed to the Artificial neural network by end of 33 weeks
- Secondary Outcome Measures
Name Time Method Artificial Neural Network predicts the gender using volumetric and linear CBCT measurements of maxillary sinusTimepoint: end of 17 weeks