Head and neck cancer researchers demonstrate the capability of a deep learning algorithm in the post-surgery setting

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Head and neck cancer researchers demonstrate the capability of a deep learning algorithm in the post-surgery setting

Artificial intelligence can augment current methods to predict the risk that head and neck cancer will spread outside the borders of neck lymph nodes, according to researchers with the ECOG-ACRIN Cancer Research Group (ECOG-ACRIN). A customized deep learning algorithm using standard computed tomography (CT) scan images and associated data contributed by patients who participated in the E3311 phase 2 trial shows promise, especially for patients with a new diagnosis of human papillomavirus (HPV)-related head and neck cancer. The E3311 validated dataset carries the potential to contribute to the more accurate staging of disease and prediction of risk.

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