Survival Prediction Of Glioblastoma Patients Using Modern Deep Learning And Machine Learning Techniques

This article discusses the use of machine learning models and a deep neural network to predict the survival outcomes of glioblastoma patients using data from the SEER database. The deep neural network consistently outperformed the machine learning models and identified age at diagnosis as the most influential feature in survival predictions. This has potential implications for aiding clinicians in decision-making for treatment and care of glioblastoma patients.