The Meta-Analysis AI in Cervical Cancer Detection and Diagnosis

One of the most important aspects of cervical cancer early diagnosis and therapy is the prompt detection of abnormal cervical cells. Computerized approaches have become a viable alternative to get beyond the drawbacks of human classification procedures, which depend on pathologists with specialized knowledge and are prone to mistakes. The purpose of this systematic review is to evaluate the diagnostic effectiveness of artificial intelligence (AI) systems about of precursory lesion detection, cervical cancer detection, and screening. The results show a notable improvement in detection reliability, with AI-based methods exhibiting predicted accuracy scores of 70% to 100% for the detection of cervix lesions that are malignant or precursory. AI is particularly good at differentiating between Pap Smears that are malignant and those that are not, with precision levels varying from 80% to 100%. AI integration offers a chance to help doctors make accurate clinical assessments, and it may wind up being a very useful tool for healthcare practice. The documented accuracy and precision of AI in diagnosing CIN2+ in the field of colposcopy, which ranged from 51.8% to 96.2% and from 71.9% to 98.22%, respectively. Notably, this study highlights the outstanding effectiveness of AI systems in prediction, screening, and detecting activities linked to cervical cancer and malignancies, even in areas with restricted access to specialized medical resources. By combining AI-enabled insights with human experience, it is possible to improve the understanding of cervical smears and pictures and ultimately improve diagnosis accuracy.