![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Open AccessCombination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients
One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So f...
-
Article
Open AccessIntegrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCC
Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) may benefit from personalised treatment, requiring biomarkers that characterize the tumour and predict treatment response. We integr...
-
Article
Open Access2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma
For treatment individualisation of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with primary radiochemotherapy, we explored the capabilities of different deep learning a...
-
Article
Open AccessA comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling
Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of differen...