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Fig. 1 | Infectious Agents and Cancer

Fig. 1

From: Assessing the risk of high-grade squamous intraepithelial lesions (HSIL+) in women with LSIL biopsies: a machine learning-based study

Fig. 1

Nomogram prediction model of missed diagnosis HSIL+ in patients with LSIL diagnosed by colposcopic biopsy. The four independent risk factors identified in the multivariate logistic regression analysis—HPV16/18 infection, TCT ≥ ASC-H, TZ3, and colposcopic impression G2—were included as final predictors in the model. Then R software was used to construct a nomogram prediction model for the risk of missed diagnosis of HSIL+. Result interpretation: each factor took a vertical line, corresponding to the top “Points” score, and then added the four factor scores to get the Total Points;Then the total score was taken as a vertical line,and the point corresponding to Risk was the risk of missed diagnosis of HSIL+

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Infectious Agents and Cancer

ISSN: 1750-9378

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