AI Webinar | Radiomics and machine learning differentiate lymph nodes in HPV+ oropharyngeal cancer

HPV+ oropharyngeal SCC presents unique imaging and disease challenges, critical for early diagnosis. This study uses radiomics and machine learning to differentiate benign and malignant lymph nodes. Retrospective analysis of 208 patients yielded 40 high-quality CT images. A random forest model trained on 80% of the data achieved an AUC of 0.97, accuracy of 87.5%, sensitivity of 66.7%, specificity of 100%, PPV of 100%, and NPV of 83.3%. Future applications may enhance diagnosis and prognosis for HPV+ oropharyngeal SCC and other HNSCC subtypes.
About Our Company
Heighten Science Publications Inc. excels in open-access publishing, focused on spreading high-quality, peer-reviewed research across diverse scientific domains. We aim to support global knowledge sharing through accessible and trustworthy academic publications