Cervical cancer screening aided by artificial intelligence, China.

Objective: To implement and evaluate a large-scale online cervical cancer screening programme in Hubei Province, China, supported by artificial intelligence and delivered by trained health workers.

Methods: The screening programme, which started in 2017, used four types of health worker: sampling health workers, slide preparation technicians, diagnostic health workers and cytopathologists. Sampling health workers took samples from the women on site; slide preparation technicians prepared slides for liquid-based cytology; diagnostic health workers identified negative samples and classified positive samples based on the Bethesda System after cytological assessment using online artificial intelligence; and cytopathologists reviewed positive samples and signed reports of the results online.

The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.

Background: Adequate cytology is limited by insufficient cytologists in a large-scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)-assisted cytology system in cervical cancer screening program.

Methods: We conducted a perspective cohort study within a population-based cervical cancer screening program for 0.

Detection of lung cancer by automated sputum cytometry.

Introduction: Biomarkers may prove to be valuable tools to manage those at risk of lung cancer. Sputum analysis using DNA cytometry has shown promise, but an automated, objective sputum analysis test has yet to be developed. This study evaluated the performance characteristics of the LungSign test for lung cancer and compared them to conventional cytology

Methods: A multicenter validation trial was conducted in which sputum specimens were prospectively collected from subjects suspected of having lung cancer during diagnostic workup.