Projects: pypi: scikit-survival
https://packages.ecosyste.ms/registries/pypi.org/packages/scikit-survival
Survival analysis built on top of scikit-learn
27 versions
Latest release: almost 2 years ago
12 dependent packages
38,483 downloads last month
Enhanced Analysis
Educational Contributors:
f.kiraly@ucl.ac.uk
hermidal@cs.umd.edu
xuyx@lamda.nju.edu.cn
Repository Activity:
Repository Owner:
Sebastian Pölsterl (user)
README Analysis:
Science Score: 100/100
Starting Score: 100 points
Bonuses:
-
+60
Educational commit emails
3 contributors with educational email addresses -
+8
Science terms in README
4 scientific terms found in README
Penalties:
-
-10
PyPI ecosystem
General-purpose ecosystem
Very Likely Science (100)
Papers Mentioning scikit-survival 8
10.1093/bioinformatics/btab039
mlr3proba: an R package for machine learning in survival analysisCited by: 38
Author(s): Raphael Sonabend, Franz J. Király, Andreas Bender, Bernd Bischl, Michel Lang
Software Mentions: 18
Published: over 4 years ago
10.1186/s13073-021-00930-x
DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics dataCited by: 72
Author(s): Olivier Poirion, Jiangbin Zheng, Kumardeep Chaudhary, Sijia Huang, Lana X. Garmire
Software Mentions: 9
Published: about 4 years ago
10.1038/s41598-021-81506-y
Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic imagesCited by: 25
Author(s): Rikiya Yamashita, Long Jin, Atif Saleem, Daniel L. Rubin, Jeanne Shen
Software Mentions: 6
Published: over 4 years ago
10.1186/s12967-020-02319-7
A LASSO-derived risk model for long-term mortality in Chinese patients with acute coronary syndromeCited by: 18
Author(s): Yiming Li, Zhuo-lun Li, Fei Chen, Qi Liu, Yong Peng, Mao Chen
Software Mentions: 4
Published: over 5 years ago
10.3390/cancers13020339
Radiomics and Dosiomics for Predicting Local Control after Carbon-Ion Radiotherapy in Skull-Base ChordomaCited by: 20
Author(s): Giulia Buizza, Chiara Paganelli, E. D’Ippolito, Giulia Fontana, Silvia Molinelli, Lorenzo Preda, Giulia Riva, Alberto Iannalfi, Francesca Valvo, Ester Orlandi, Guido Baroni
Software Mentions: 3
Published: over 4 years ago
10.1186/s13062-019-0249-6
A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction modelsCited by: 33
Author(s): Iliyan Mihaylov, Maciej M. Kańduła, Milko Krachunov, Dimitar Vassilev
Software Mentions: 3
Published: over 5 years ago
10.3390/jcm10153308
Usefulness of a Hepatitis B Surface Antigen-Based Model for the Prediction of Functional Cure in Patients with Chronic Hepatitis B Virus Infection Treated with Nucleos(t)ide Analogues: A Real-World StudyCited by: 5
Author(s): Gian Paolo Caviglia, Yulia Troshina, Enrico Garro, M. Gesualdo, Serena Aneli, Giovanni Birolo, Fabrizia Pittaluga, Rossana Cavallo, Giorgio Maria Saracco, Alessia Ciancio
Software Mentions: 2
Published: about 4 years ago
10.1038/s41598-021-86327-7
Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survivalCited by: 96
Author(s): Arturo Moncada‐Torres, Marissa C. van Maaren, Mathijs P. Hendriks, Sabine Siesling, Gijs Geleijnse
Software Mentions: 1
Published: over 4 years ago