AI for Cervical Cancer Identification

The chances of avoiding cervical cancer are improved by early detection of abnormal cells in the cervix. Automated methods were created because manual detection, which involves specialized pathologists and is time-consuming and prone to mistake, is not a practical or effective method for detecting abnormal cervical cells. comprehensive analysis of AI-based methods for cervical precancerous cancer detection, screening, and prognosis. Sources and approach of the search: To find publications published up to July 2022, a thorough search of Medline and the Science Core Collection site was conducted (to maximize Scopus coverage). Papers using artificial intelligence (AI) models for cervical cancer detection, diagnosis, and prediction will be included in our analysis. The era of lock-in did not exist. According to the disclosure requirements of systematic reviews and meta-analyses, studies on technician iEPI usage were located and evaluated for quality and relevance. Results: 2538 items were found in the first search. After examination, the 117 papers that were included in the review were deemed eligible. On the other hand, it was discovered that pelvic lesions should be checked for tumors and precancerous disorders using AI technology in order to create screening software that runs automatically. The predictive accuracy of the algorithm for cervical cancer ranged from 70% to 100%. This indicates that artificial intelligence (AI) systems can distinguish between benign and malignant cervical cytology with an accuracy range of 80–100%. AI as a clinical diagnostic tool for doctors: The sensitivity of AI in detecting CIN2+ in colposcopy was 71. 9–98. with a specificity of 51 and 22%. 8–96. 2%. This work demonstrates that AI systems can predict the existence of precancerous lesions and cervical cancer using cytology slides in a situation where access to specialized facilities and healthcare is restricted. It's been demonstrated. Artificial intelligence (AI) might be a helpful supplement to human judgment when it comes to the interpretation of cervical smears and pictures.