Results comparison of cervical cancer early detection using cerviray ® with VIA test.

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES BMC Research Notes Pub Date : 2025-01-22 DOI:10.1186/s13104-025-07086-6

Ali Budi Harsono, Hadi Susiarno, Dodi Suardi, Kemala Isnainiasih Mantilidewi, Viko Duvadilan Wibowo, Yudi Mulyana Hidayat

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引用次数: 0

Abstract

Objectives: This study investigates the performance of artificial intelligence (AI) technology, namely Cerviray AI^®, compared with Cerviray^® expert, aiming to compare its sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC ROC). The Visual Inspection with Acetic Acid (VIA) test is used as the gold standard.

Results: The study involved 44 patients from various health centers in West Java Province. Performance of Cerviray AI^®, or Cerviray^® expert, and lastly VIA tests were compared in their ability to detect pre-cancerous cervical lesions in high-risk women of childbearing age. The current study indicated that Cerviray AI^® had a sensitivity of 42.9%, specificity of 100%, PPV of 100%, and ROC AUC values of 71.4%. In comparison, the evaluation of the Cerviray^® expert demonstrated a sensitivity of 71.4%, specificity of 97.3%, PPV of 83.3%, and ROC AUC values of 84.4%. In conclusion, the evaluation of Cerviray^® expert outperformed Cerviray AI^® in ROC AUC values.

Trial registration: Clinical Trials.gov Identifier NCT06518070 Retrospectively registered.

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来源期刊

BMC Research Notes Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)

CiteScore

3.60

自引率

0.00%

发文量

363

审稿时长

15 weeks

期刊介绍： BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.