Objectives: We tested the ability of automated screening in processing conventional gynecological cytology smears and its efficacy in assessing sample adequacy and stratifying cases for risk of malignancy. Study Design: Cases were retrospectively selected, including unsatisfactory samples and slides with various sorts of artifacts. Automated screening was performed using the FocalPoint GS Imaging System (Becton Dickinson, Franklin Lakes, N.J., USA), with classification into five quintiles. For agreement purposes, cases were grouped into high risk for malignancy (quintiles 1 and 2) and low risk for malignancy (quintiles 3, 4 and 5). Results: A total of 120 cases (median age 37.5 years, range 18-85) were included in the study. Eighty-three cases (69.2%) could be successfully classified into quintiles. When divided by risk, 31 cases were placed in the high-risk and 52 in the low-risk group. The overall sensitivity and specificity of the automated analysis was 100 and 70.3%, respectively. Conclusions: Automated analysis could analyze the majority of conventional smears, including one case previously screened as unsatisfactory. All malignant and high-grade lesions were correctly classified into the high-risk group. Broad use of this automation system could potentially decrease screening time and augment the efficacy in detecting precursor neoplastic changes in cervical cytology smears.