Machine Learning Screening
Machine Learning Screening is a computational methodology within the domain of systematic study selection that employs machine learning algorithms to automatically identify, classify, or prioritize scholarly records for inclusion in academic research, distinguished by its reliance on data-driven models to enhance the efficiency and accuracy of screening processes.
133
Publications
8.1K
Citations
710
Authors
325
Institutions
Publications per year
2017–2026
121
133
SWIFT-Review: a text-mining workbench for systematic review
Brian E. Howard, Jason Phillips, Kyle J. Miller et al. · Systematic Reviews · 2016 · 191 citations · Full text
Byron Wallace, Anna H Noel-Storr, Iain Marshall et al. · Journal of the American Medical Informatics Association · 2017 · 191 citations · Full text
Autism Spectrum Disorder Screening
Fadi Thabtah · 2017 · 190 citations
1–5 of 133
710
4
h-index
4
h-index
4
h-index
4
h-index
3
h-index
1–5 of 710
325
Utrecht University
Utrecht, The Netherlands
5 h-index
43 publications
20.4K citations
Abdul Wali Khan University Mardan
Mardan, Pakistan
4 h-index
12 publications
579 citations

University of Alberta
Edmonton, Canada
4 h-index
24 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
182 citations

Sichuan University
Chengdu, China
3 h-index
19 publications
857 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
12 publications
382 citations
Umm al-Qura University
Makkah al Mukarramah, Saudi Arabia
3 h-index
4 publications
142 citations

Polish Academy of Sciences
Warsaw, Poland
3 h-index
6 publications
343 citations
1–8 of 325
12 publications · 1.2K citations
12
h-index
4 publications · 213 citations
4
h-index
4 publications · 391 citations
4
h-index
3 publications · 72 citations
3
h-index
3 publications · 71 citations
3
h-index
1–5