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Papers: 10.1186/s13643-019-0942-7

https://doi.org/10.1186/s13643-019-0942-7

Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error

Cited by: 86
Author(s): Alexandra Bannach‐Brown, Piotr Przybyła, James Thomas, Andrew S.C. Rice, Sophia Ananiadou, Jing Liao, Malcolm Macleod
Published: over 6 years ago

Software Mentions 8

cran: caret
Classification and Regression Training
Papers that mentioned: 630
Very Likely Science (100)
cran: fmsb
Functions for Medical Statistics Book with some Demographic Data
Papers that mentioned: 111
Very Likely Science (85)
cran: glmnet
Lasso and Elastic-Net Regularized Generalized Linear Models
Papers that mentioned: 1,607
Very Likely Science (100)
cran: pROC
Display and Analyze ROC Curves
Papers that mentioned: 1,740
Very Likely Science (95)
pypi: caret
A Python Interface to Asterisk
Papers that mentioned: 630
Very Likely Science (65)
pypi: excel
This package name is reserved by Microsoft Corporation
Papers that mentioned: 2,995
Unlikely Science (5)
pypi: glmnet
Python wrapper for glmnet
Papers that mentioned: 1,607
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)