Classification of Non-Small Lung Carcinoma Using Ai based algorithm
Not Applicable
- Conditions
- Health Condition 1: J984- Other disorders of lung
- Registration Number
- CTRI/2024/03/064671
- Lead Sponsor
- Department of Radiodiagnosis and Imaging
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
Patients with CT imaging features of Squamous cell carcinoma and Adenocarcinoma.
Exclusion Criteria
Patients with histopathologic diagnosis of small cell carcinoma
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method The machine learning methods based on CT radiomic features can be used to classify Non-Small Cell Lung Carcinoma subtypes using a simple, non-invasive, and cost-effective diagnostic approach <br/ ><br>Timepoint: Scan will be performed after biopsy
- Secondary Outcome Measures
Name Time Method Machine learning methods based on CT radiomic features can provide non-invasive diagnosis of classification of Non-Small Cell Lung Carcinoma. <br/ ><br>Timepoint: scan will be performed after biopsy