https://ojs.bbwpublisher.com/index.php/PAR/issue/feedProceedings of Anticancer Research2025-01-16T15:13:35+08:00Seven Gaoinfo@bbwpublisher.comOpen Journal Systems<p style="text-align: justify;"><em>Proceedings of Anticancer Research (PAR) </em>is an international peer-reviewed and open access journal, which is devoted to the rapid publication of high-quality original articles, reviews, case reports, short communication and letters on all aspects of experimental and clinical oncology.</p> <p style="text-align: justify;">The covered topics include, but are not limited to: cellular research and bio-markers, identification of bio-targets and agents with novel mechanisms of action, preventative and integrated treatments for cancer patients, radiation and surgery, palliative care, patient adherence, quality of life, satisfaction, and anticancer medicine, anticancer agents, novel therapies in development, cancer management, biomarkers, diagnostics, clinical trials, treatment guidelines.</p> <p align="justify"> </p>https://ojs.bbwpublisher.com/index.php/PAR/article/view/9386Application Value of Artificial Intelligence-Assisted Diagnostic Systems in CT Diagnosis of Pulmonary Nodules2025-01-16T15:13:35+08:00Yang Xue26917269@qq.comMingqiang Diao26917269@qq.comBing Han26917269@qq.com<p><strong><em>Objective</em></strong><em>:</em> To explore the application value of artificial intelligence-assisted diagnostic systems in the computed tomography (CT) diagnosis of pulmonary nodules. <strong><em>Methods</em></strong><em>:</em> A total of 80 patients with pulmonary nodules, treated from June 2023 to May 2024, were included. All patients underwent pathological examination and CT scans, with pathological results serving as the gold standard. The diagnostic performance of CT alone and CT combined with the artificial intelligence-assisted diagnostic system was analyzed, and differences in CT imaging features and evaluation results of benign and malignant pulmonary nodules were compared. <strong><em>Results</em></strong><em>:</em> The sensitivity, specificity, and accuracy of CT combined with the artificial intelligence-assisted diagnostic system were significantly higher than those of CT alone (<em>P</em> < 0.05). Moreover, the false-positive and false-negative rates were significantly lower for the combined approach compared to CT alone (<em>P</em> < 0.05). <strong><em>Conclusion</em></strong><em>:</em> The artificial intelligence-assisted diagnostic system effectively identifies malignant features in pulmonary nodules, providing valuable clinical reference data and enhancing diagnostic accuracy and efficiency.</p>2025-01-16T15:00:45+08:00Copyright (c) 2025 Author(s)