Article

Machine learning based predictive model of early mortality in stage III and IV prostate cancer

2020-04-18

Abstract excerpt

Prostate cancer remains the third highest cause of cancer-related deaths. Metastatic prostate cancer could yield poor prognosis, however there is limited work on predictive models for clinical decision support in stage III and IV prostate cancer. We developed a machine learning model for predicting early mortality in prostate cancer (survival less than 21 months after initial diagnosis). A cohort of 10,303 patient...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7a0f408d-4937-582f-a04c-d332b081c505
DOI: 10.1101/2020.04.15.20065938

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Machine learning based predictive model of early mortality in stage III and IV prostate cancerDOI 10.1101/2020.04.15.20065938Read

Machine learning algorithm for early mortality prediction in patients with advanced penile cancerSemantic proximity Read

Comprehensive evaluation of machine learning models and gene expression signatures for prostate cancer prognosis using large population cohortsSemantic proximity Read

VALIDATION OF PROGRESS, A SIMPLE MACHINE-LEARNING DERIVED RISK STRATIFICATION SCORE FOR CASTRATION-RESISTANT PROSTATE CANCERSemantic proximity Read

Survival prognosis and variable selection: A case study for metastatic castrate resistant prostate cancer patientsSemantic proximity Read

A bibliometric analysis of use of Machine learning and Artificial intelligence in Prostate Cancer DetectionSemantic proximity Read

Application of machine learning methods to predict progression in patients with hormone-sensitive prostate cancerSemantic proximity Read

Identification and validation of a prognostic 5-protein signature for biochemical recurrence following radical prostatectomy in prostate cancerSemantic proximity Read

Genomic Classifiers and Prognosis of Localized Prostate Cancer: A Systematic ReviewSemantic proximity Read

A five‐microRNA model (pCaP) for predicting prostate cancer aggressiveness using cell‐free urineSemantic proximity Read

ProCanBio: a database of manually curated biomarkers for Prostate CancerSemantic proximity Read

Identifying patients with rapid progression from hormone-sensitive to castration-resistant prostate cancer: a retrospective studySemantic proximity Read

Identification of prognostic markers of high grade prostate cancer through an integrated bioinformatics approachSemantic proximity Read