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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Prediction of Probable Major Depressive Disorder in the Taiwan Biobank: An Integrated Machine Learning and Genome-Wide Analysis Approach
Eugene Lin, Po‐Hsiu Kuo, Wan‐Yu Lin, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 7, pp. 597-597
Open Access | Times Cited: 9

Showing 9 citing articles:

Deep Learning with Neuroimaging and Genomics in Alzheimer’s Disease
Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 15, pp. 7911-7911
Open Access | Times Cited: 52
Identifying Depression Through Machine Learning Analysis of Omics Data: A Scoping Review (Preprint)
Brittany Taylor, Mollie Hobensack, Stephanie Niño de Rivera, et al.
JMIR Nursing (2024) Vol. 7, pp. e54810-e54810
Open Access | Times Cited: 2
MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach
Yee Ling Chan, Cyrus S. H. Ho, Gabrielle W. N. Tay, et al.
Journal of Affective Disorders (2024) Vol. 360, pp. 326-335
Closed Access | Times Cited: 1
Healthcare data quality assessment for improving the quality of the Korea Biobank Network
Kihoon Kim, Seol Whan Oh, SooJeong Ko, et al.
PLoS ONE (2023) Vol. 18, Iss. 11, pp. e0294554-e0294554
Open Access | Times Cited: 2
The cysteine-altering p.R544C variant in the NOTCH3 gene is a probable candidate for blood pressure and relevant traits in the Taiwan Biobank
Eugene Lin, Po‐Hsiu Kuo, Yu‐Li Liu, et al.
Journal of Neurology (2023) Vol. 270, Iss. 11, pp. 5536-5544
Closed Access | Times Cited: 1
Diagnosis of Mental Illness Using Deep Learning: A Survey
Sindhu Rajendran, R.R. Rubia Gandhi, S. Smruthi, et al.
Intelligent systems reference library (2023), pp. 223-244
Closed Access | Times Cited: 1
Deep Learning Tactics for Neuroimaging Genomics Investigations in Alzheimer's Disease
Mithun Singh Rajput, Jigna Shah, Viral Patel, et al.
(2024), pp. 451-471
Closed Access
Predicting drug responsiveness by citalopram induced pathway regulations and biomarker discovery in lymphoblastoid cell lines from depression affected individuals
Karthik Sekaran, S. Shanmugam
2021 International Conference on Decision Aid Sciences and Application (DASA) (2021), pp. 267-271
Closed Access | Times Cited: 1
Identifying Depression Through Machine Learning Analysis of Omics Data: A Scoping Review (Preprint)
Brittany Taylor, Mollie Hobensack, Stephanie Niño de Rivera, et al.
(2023)
Closed Access
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