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:
Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity
Shengli Chen, Xiaojing Zhang, Shiwei Lin, et al.
Journal of Affective Disorders (2022) Vol. 322, pp. 173-179
Closed Access | Times Cited: 7
Shengli Chen, Xiaojing Zhang, Shiwei Lin, et al.
Journal of Affective Disorders (2022) Vol. 322, pp. 173-179
Closed Access | Times Cited: 7
Showing 7 citing articles:
Machine learning and the prediction of suicide in psychiatric populations: a systematic review
Alessandro Pigoni, Giuseppe Delvecchio, Nunzio Turtulici, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 26
Alessandro Pigoni, Giuseppe Delvecchio, Nunzio Turtulici, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 26
Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder
Kun Qin, Huiru Li, Huawei Zhang, et al.
Biological Psychiatry (2024) Vol. 96, Iss. 6, pp. 435-444
Closed Access | Times Cited: 12
Kun Qin, Huiru Li, Huawei Zhang, et al.
Biological Psychiatry (2024) Vol. 96, Iss. 6, pp. 435-444
Closed Access | Times Cited: 12
Classification of suicidality by training supervised machine learning models with brain MRI findings: A systematic review
Mohammadamin Parsaei, Fateme Taghavizanjani, Giulia Cattarinussi, et al.
Journal of Affective Disorders (2023) Vol. 340, pp. 766-791
Closed Access | Times Cited: 14
Mohammadamin Parsaei, Fateme Taghavizanjani, Giulia Cattarinussi, et al.
Journal of Affective Disorders (2023) Vol. 340, pp. 766-791
Closed Access | Times Cited: 14
Classification of female MDD patients with and without suicidal ideation using resting-state functional magnetic resonance imaging and machine learning
Morteza Fattahi, Milad Esmaeil-Zadeh, Hamid Soltanian‐Zadeh, et al.
Frontiers in Human Neuroscience (2025) Vol. 18
Open Access
Morteza Fattahi, Milad Esmaeil-Zadeh, Hamid Soltanian‐Zadeh, et al.
Frontiers in Human Neuroscience (2025) Vol. 18
Open Access
Identification of Subthreshold Depression Based on fNIRS–VFT Functional Connectivity: A Machine Learning Approach
Lin Li, Jingxuan Liu, Yifan Zheng, et al.
Depression and Anxiety (2025) Vol. 2025, Iss. 1
Open Access
Lin Li, Jingxuan Liu, Yifan Zheng, et al.
Depression and Anxiety (2025) Vol. 2025, Iss. 1
Open Access
A predictive study of the efficacy of transcutaneous auricular vagus nerve stimulation in the treatment of major depressive disorder: an fMRI-based machine learning analysis
Jifei Sun, Kai Sun, Li-Mei Chen, et al.
Asian Journal of Psychiatry (2024) Vol. 98, pp. 104079-104079
Open Access | Times Cited: 1
Jifei Sun, Kai Sun, Li-Mei Chen, et al.
Asian Journal of Psychiatry (2024) Vol. 98, pp. 104079-104079
Open Access | Times Cited: 1
A multimodal prediction model for suicidal attempter in major depressive disorder
Qiaojun Li, Kun Liao
PeerJ (2023) Vol. 11, pp. e16362-e16362
Open Access | Times Cited: 3
Qiaojun Li, Kun Liao
PeerJ (2023) Vol. 11, pp. e16362-e16362
Open Access | Times Cited: 3
