Diagnostic Accuracy of Machine Learning for Classifying Benign and Malignant Pulmonary Nodules — A Systematic Review and Diagnostic Test Accuracy Meta-analysis

This component contains the study protocol for a systematic review and diagnostic test accuracy (DTA) meta-analysis evaluating the performance of machine learning and deep learning models for differentiating benign and malignant pulmonary nodules. The protocol describes the research objectives, eligibility criteria, search strategy, study selection process, data extraction, risk-of-bias assessment using QUADAS-2, and planned statistical analyses including pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and summary receiver operating characteristic (SROC) analyses. The review will follow PRISMA 2020 and PRISMA-DTA reporting guidelines.