Kelley Paskov
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Explore the profile of Kelley Paskov including associated specialties, affiliations and a list of published articles.
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20
Citations
414
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Recent Articles
1.
Paskov K, Chrisman B, Stockham N, Washington P, Dunlap K, Jung J, et al.
Genome Res
. 2023 Oct;
33(10):1747-1756.
PMID: 37879861
Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS...
2.
Chrisman B, He C, Jung J, Stockham N, Paskov K, Washington P, et al.
Genome Res
. 2023 Oct;
33(10):1734-1746.
PMID: 37879860
Although it is ubiquitous in genomics, the current human reference genome (GRCh38) is incomplete: It is missing large sections of heterochromatic sequence, and as a singular, linear reference genome, it...
3.
Liu B, Paskov K, Kent J, McNealis M, Sutaria S, Dods O, et al.
JAMA Netw Open
. 2023 Jan;
6(1):e2251182.
PMID: 36689227
Importance: While research has identified racial and ethnic disparities in access to autism services, the size, extent, and specific locations of these access gaps have not yet been characterized on...
4.
Chrisman B, He C, Jung J, Stockham N, Paskov K, Wall D
Virol J
. 2022 Dec;
19(1):225.
PMID: 36566197
While hundreds of thousands of human whole genome sequences (WGS) have been collected in the effort to better understand genetic determinants of disease, these whole genome sequences have less frequently...
5.
Chrisman B, He C, Jung J, Stockham N, Paskov K, Washington P, et al.
Sci Rep
. 2022 Jun;
12(1):9863.
PMID: 35701436
The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using...
6.
Washington P, Kalantarian H, Kent J, Husic A, Kline A, Leblanc E, et al.
Cognit Comput
. 2022 Jun;
13(5):1363-1373.
PMID: 35669554
Background/introduction: Emotion detection classifiers traditionally predict discrete emotions. However, emotion expressions are often subjective, thus requiring a method to handle compound and ambiguous labels. We explore the feasibility of using...
7.
Washington P, Chrisman B, Leblanc E, Dunlap K, Kline A, Mutlu C, et al.
Intell Based Med
. 2022 May;
6.
PMID: 35634270
Artificial Intelligence (A.I.) solutions are increasingly considered for telemedicine. For these methods to serve children and their families in home settings, it is crucial to ensure the privacy of the...
8.
Stockham N, Washington P, Chrisman B, Paskov K, Jung J, Wall D
JMIR Public Health Surveill
. 2022 May;
8(7):e31306.
PMID: 35605128
Background: Selection bias and unmeasured confounding are fundamental problems in epidemiology that threaten study internal and external validity. These phenomena are particularly dangerous in internet-based public health surveillance, where traditional...
9.
Washington P, Kalantarian H, Kent J, Husic A, Kline A, Leblanc E, et al.
JMIR Pediatr Parent
. 2022 Apr;
5(2):e26760.
PMID: 35394438
Background: Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However, most computer vision emotion recognition models are trained...
10.
Varma M, Washington P, Chrisman B, Kline A, Leblanc E, Paskov K, et al.
J Med Internet Res
. 2022 Feb;
24(2):e31830.
PMID: 35166683
Background: Autism spectrum disorder (ASD) is a widespread neurodevelopmental condition with a range of potential causes and symptoms. Standard diagnostic mechanisms for ASD, which involve lengthy parent questionnaires and clinical...