Evaluation of machine learning model for auto assessment of cervical health using Smart Scope
Not Applicable
- Registration Number
- CTRI/2019/09/021261
- Lead Sponsor
- Periwinkle Technologies Pvt Ltd
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
1. Sexually active women
2. Age between 25 and 65 years
3. Those who have volunteered for Smart Scope test in routine OPD or in specially arranged health camps
Exclusion Criteria
1. Pregnant women
2. Women with prior colposcopy or any other cervical / vaginal / uterine procedure done within the last one month
3. Women with vaginal bleeding or earlier known frank cancer
4. Women who have had hysterectomy
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Auto assessment and manual assessment of digital images obtained using Smart Scope into three categories viz., normal (green) / abnormal benign changes (amber) / pre-cancerous & cancerous changes (red).Timepoint: Immediately after screening by VIA with 5% Acetic acid and VILI by Lugols Iodine
- Secondary Outcome Measures
Name Time Method Categorization by auto assessment of digital images of VIA-VILITimepoint: During Smart Scope aided VIA-VILI Test;Categorization into three categories ie. Green/ Amber/ Red among women screened by manual assessment of digital VIA-VILI imagesTimepoint: During Smart Scope aided VIA-VILI Test;Confirmation of CIN and CA cases by conventional colposcopyTimepoint: During standard colposcopy;Histopathology confirmed Cervical Intraepithelial neoplasiaTimepoint: After histo-pathology report of sample taken during colpo-guided biopsy