Prostate cancer—personalized response prediction

Prostate cancer radiomics: A study on IMRT response prediction based on MR image features and machine learning approaches

Introduction: To develop different radiomic models based on radiomic features and machine learning methods to predict early intensity modulated radiation therapy (IMRT) response.   Materials and Methods: Thirty prostate patients were included. All patients underwent pre ad post-IMRT T2 weighted and apparent diffusing coefficient (ADC) magnetic resonance imagi...

Personalized prediction of tumor response and cancer progression on prostate needle biopsy.

PURPOSE To our knowledge in patients with prostate cancer there are no available tests except clinical variables to determine the likelihood of disease progression. We developed a patient specific, biology driven tool to predict outcome at diagnosis. We also investigated whether biopsy androgen receptor levels predict a durable response to therapy after secondary treatment. MATERIALS AND METH...

Structured Prediction of Network Response

We introduce the network response problem (Su et al. 2014): given a network G = (V,E) and an action a, predict the subnetworkGa = (Va, Ea) that responses to the action, that is, which nodes v ∈ Va perform the action, and which directed edges e = (v, u) ∈ Ea relay the action from v to an adjacency node u. We assume that G is directed, and any undirected network can be seen as a special case. We ...

Complete Radiologic Response in Metastatic Castration-Resistant Prostate Cancer Treated with Cabazitaxel

Corrigendum: Drug Response Prediction as a Link Prediction Problem

This Article contains a typographical error in the Results section under the subheading 'Method Comparison'. " In order to better understand the accuracy of our method, we compare it against the top performing approach in the DREAM Drug Sensitivity Prediction Challenge, Gonen and Margolin's kernelized Bayesian multitask learning (KBMTL) algorithm 19 ". should read: " In order to better understa...