27Jun 2023
Machine learning in laryngeal cancer: A pilot study to predict oncological outcomes and the role of adverse features

Machine learning in laryngeal cancer: A pilot study to predict oncological outcomes and the role of adverse features

This study explored the use of Machine Learning (ML) algorithms to predict 1- and 3-year overall survival (OS) in patients with laryngeal carcinoma (LC). A dataset of 132 patients was analyzed, and a decision-tree algorithm achieved high accuracy in predicting survival rates (95% for 1-year and 82.5% for 3-year). Important prognostic factors included lymph node ratio, type of surgery, subsite, number of metastases, perineural invasion, and grading. The findings suggest that integrating ML into medical practices has the potential to revolutionize the approach to cancer pathology.

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