TY  - JOUR
AU  - Kebede, Mihiretu
AU  - Le Cornet, Charlotte
AU  - Turzanski-Fortner, Renée
TI  - In-depth evaluation of machine learning methods for semi-automating article screening in a systematic review of mechanistic literature.
JO  - Cordis
VL  - 14
IS  - 2
SN  - 1759-2879
CY  - Sao Paulo
PB  - Programa de Estudos Pós-Graduados em História
M1  - DKFZ-2022-01433
SP  - 156-172
PY  - 2023
N1  - #EA:C020#LA:C020# / 2023 Mar;14(2):156-172
AB  - We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic review. Overall, 16,430 manually screened titles/abstracts, including 861 references identified relevant for full-text review were used for the analysis. Of these, 40
KW  - Automated screening (Other)
KW  - Citation Screening (Other)
KW  - Machine Learning (Other)
KW  - NLP (Other)
KW  - Natural Language Processing (Other)
KW  - Systematic review (Other)
KW  - Text mining (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:35798691
DO  - DOI:10.1002/jrsm.1589
UR  - https://inrepo02.dkfz.de/record/180603
ER  -