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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:

Machine Learning and Deep Learning for the Pharmacogenomics of Antidepressant Treatments
Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane
Clinical Psychopharmacology and Neuroscience (2021) Vol. 19, Iss. 4, pp. 577-588
Open Access | Times Cited: 20

Showing 20 citing articles:

From promise to practice: towards the realisation of AI-informed mental health care
Nikolaos Koutsouleris, Tobias U. Hauser, Vasilisa Skvortsova, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 11, pp. e829-e840
Open Access | Times Cited: 131
Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology
Ajay Vikram Singh, Vaisali Chandrasekar, Namuna Paudel, et al.
Biomedicine & Pharmacotherapy (2023) Vol. 163, pp. 114784-114784
Open Access | Times Cited: 84
AI's role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy
Hamed Taherdoost, Alireza Ghofrani
Intelligent Pharmacy (2024) Vol. 2, Iss. 5, pp. 643-650
Open Access | Times Cited: 18
Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders
Samradhi Singh, Devojit Kumar Sarma, Vinod Verma, et al.
Biochemical and Biophysical Research Communications (2023) Vol. 682, pp. 1-20
Closed Access | Times Cited: 41
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
De Novo Peptide and Protein Design Using Generative Adversarial Networks: An Update
Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 4, pp. 761-774
Closed Access | Times Cited: 32
Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal
Seyed Morteza Mirjebreili, Reza Shalbaf, Ahmad Shalbaf
Physical and Engineering Sciences in Medicine (2024) Vol. 47, Iss. 2, pp. 633-642
Open Access | Times Cited: 6
Validating the accuracy of mathematical model–based pharmacogenomics dose prediction with real-world data
Yolande Saab, Zahi Nakad
European Journal of Clinical Pharmacology (2025)
Closed Access
Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning‐Based Advanced Perspectives
Sung‐Hyun Kim, Sumin Yang, Jeehye Jung, et al.
Advanced Science (2025)
Open Access
Precision Psychiatry for Obsessive-Compulsive Disorder: Clinical Applications of Deep Learning Architectures
Brian A. Zaboski, Lora Bednarek
Journal of Clinical Medicine (2025) Vol. 14, Iss. 7, pp. 2442-2442
Open Access
Machine learning, pharmacogenomics, and clinical psychiatry: predicting antidepressant response in patients with major depressive disorder
William V. Bobo, Bailey Van Ommeren, Arjun P. Athreya
Expert Review of Clinical Pharmacology (2022) Vol. 15, Iss. 8, pp. 927-944
Closed Access | Times Cited: 14
Evaluation of supervised machine learning algorithms in predicting the poor anticoagulation control and stable weekly doses of warfarin
Kannan Sridharan, Murali Ramanathan, Rashed Al Banna
International Journal of Clinical Pharmacy (2022) Vol. 45, Iss. 1, pp. 79-87
Closed Access | Times Cited: 7
Artificial intelligence in the detection and treatment of depressive disorders: a narrative review of literature
Fabiana Ricci, Daniela Giallanella, Costanza Gaggiano, et al.
International Review of Psychiatry (2024), pp. 1-13
Closed Access | Times Cited: 1
Postphenomenology and Human Constitutive Technicity
Marco Pavanini
Journal of Human-Technology Relations (2024) Vol. 2, pp. 1-25
Closed Access | Times Cited: 1
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
Machine Learning Algorithms for the Prediction of Locomotor Activity by an Infrared Motion Detector on the Sleep-wake States in Mice
Yoo Rha Hong, Kyungwon Kim, Eunsoo Moon, et al.
Clinical Psychopharmacology and Neuroscience (2023) Vol. 21, Iss. 2, pp. 279-287
Open Access | Times Cited: 2
Prediction of Treatment Response in Major Depressive Disorder using a Hybrid of Convolutional Recurrent Deep Neural Networks and Effective connectivity based on EEG Signal
Seyed Morteza Mirjebreili, Reza Shalbaf, Ahmad Shalbaf
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Application of computer on Pharmacogenomics
Muhammed Amanat, Randhir Singh
Bangladesh Journal of Medical Science (2024) Vol. 23, Iss. 2, pp. 300-308
Open Access
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
Artificial Intelligence in the Clinical Laboratory
Jason M. Baron
Clinics in Laboratory Medicine (2022) Vol. 43, Iss. 1, pp. 1-16
Closed Access | Times Cited: 2
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