Applicant Misrepresentation Detection
Applicant Misrepresentation Detection is a methodological framework within background screening that identifies deliberate falsifications or omissions in an applicant's credentials or statements through systematic validation and anomaly detection.
19
Publications
1.1K
Citations
72
Authors
48
Institutions
Publications per year
2017–2026
2
Parents
19
1–5 of 19
72
University of Arkansas for Medical Sciences, United States
2 publications · 45 citations
2
h-index
2
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2
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1
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1
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1–5 of 72
48

Florida Institute of Technology
Melbourne, United States
2 h-index
5 publications
309 citations
Seattle University
Seattle, United States
2 h-index
7 publications
290 citations
University of Washington
Seattle, United States
2 h-index
7 publications
290 citations
Sunovion (United Kingdom)
London, United Kingdom
1 h-index
1 publications
195 citations
University of Virginia
Charlottesville, United States
1 h-index
5 publications
490 citations

Mount Sinai Beth Israel
New York, United States
1 h-index
4 publications
40 citations

University of Arkansas for Medical Sciences
Little Rock, United States
1 h-index
1 publications
29 citations

Virginia Commonwealth University Medical Center
Richmond, United States
1 h-index
1 publications
23 citations
1–8 of 48
1 publications · 29 citations
1
h-index
1 publications · 36 citations
1
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1 publications · 25 citations
1
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AJR · 1 publications · 43 citations
1
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1 publications · 98 citations
1
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1–5