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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 classification of ADHD and HC by multimodal serotonergic data
Alexander Kautzky, Thomas Vanicek, C. Philippe, et al.
Translational Psychiatry (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Multimodal machine learning in precision health: A scoping review
Adrienne Kline, Hanyin Wang, Yikuan Li, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 212
Automated detection of ADHD: Current trends and future perspective
Hui Wen Loh, Chui Ping Ooi, Prabal Datta Barua, et al.
Computers in Biology and Medicine (2022) Vol. 146, pp. 105525-105525
Open Access | Times Cited: 103
Multimodal Classification: Current Landscape, Taxonomy and Future Directions
William C. Sleeman, Rishabh Kapoor, Preetam Ghosh
ACM Computing Surveys (2022) Vol. 55, Iss. 7, pp. 1-31
Open Access | Times Cited: 74
Toward Precision Medicine in ADHD
Jan K. Buitelaar, Sven Bölte, Daniel Brandeis, et al.
Frontiers in Behavioral Neuroscience (2022) Vol. 16
Open Access | Times Cited: 42
Effects of music therapy as an alternative treatment on depression in children and adolescents with ADHD by activating serotonin and improving stress coping ability
Jong-In Park, In-Ho Lee, Seung‐Jea Lee, et al.
BMC Complementary Medicine and Therapies (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 36
Individualized prediction models in ADHD: a systematic review and meta-regression
Gonzalo Salazar de Pablo, Raquel Iniesta, Alessio Bellato, et al.
Molecular Psychiatry (2024) Vol. 29, Iss. 12, pp. 3865-3873
Open Access | Times Cited: 7
An algorithm for using deep learning convolutional neural networks with three dimensional depth sensor imaging in scoliosis detection
Terufumi Kokabu, Satoshi Kanai, Noriaki Kawakami, et al.
The Spine Journal (2021) Vol. 21, Iss. 6, pp. 980-987
Open Access | Times Cited: 39
Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach
Miguel Garcia‐Argibay, Yanli Zhang‐James, Samuele Cortese, et al.
Molecular Psychiatry (2022) Vol. 28, Iss. 3, pp. 1232-1239
Open Access | Times Cited: 27
Laying the groundwork: Exploring pesticide exposure and genetic factors in south-eastern Brazilian farmers
Débora Dummer Meira, Victor Nogueira da Gama Kohls, Matheus Correia Casotti, et al.
Current Research in Toxicology (2025) Vol. 8, pp. 100215-100215
Open Access
ATTENTION DEFICIT HYPERACTIVITY DISORDER IDENTIFICATION: fMRI DATA ANALYZED with CNN and SEED-BASED APPROACH
Anika Siamin Oyshi, Mohammad Jahid Hasan, Mohsin Y Ahmed, et al.
Brain Disorders (2025), pp. 100198-100198
Open Access
Local interpretable model-agnostic explanations guided brain magnetic resonance imaging classification for identifying attention deficit hyperactivity disorder subtypes
K. Usha Rupni, P. Aruna Priya
Journal of Ambient Intelligence and Humanized Computing (2025)
Closed Access
Machine learning-enabled multiplexed microfluidic sensors
Sajjad Rahmani Dabbagh, Fazle Rabbi, Zafer Doğan, et al.
Biomicrofluidics (2020) Vol. 14, Iss. 6, pp. 061506-061506
Open Access | Times Cited: 36
Use of machine learning to classify adult ADHD and other conditions based on the Conners’ Adult ADHD Rating Scales
Hanna Christiansen, Mira‐Lynn Chavanon, Oliver Hirsch, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 34
Investigating the impact of standard brain atlases and connectivity measures on the accuracy of ADHD detection from fMRI data using deep learning
Snigdha Agarwal, Adarsh Raj, Anjan Chowdhury, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 25, pp. 67023-67057
Closed Access | Times Cited: 4
Classifying Children with ADHD Based on Prefrontal Functional Near-infrared Spectroscopy Using Machine Learning
Chan-Mo Yang, Jaeyoung Shin, Johanna Inhyang Kim, et al.
Clinical Psychopharmacology and Neuroscience (2023) Vol. 21, Iss. 4, pp. 693-700
Open Access | Times Cited: 10
The Impact of Genetics on Cognition: Insights into Cognitive Disorders and Single Nucleotide Polymorphisms
Giulia Spoto, Gabriella Di Rosa, Antonio Gennaro Nicotera
Journal of Personalized Medicine (2024) Vol. 14, Iss. 2, pp. 156-156
Open Access | Times Cited: 3
ADHDNet: A DNN Based Framework for Efficient ADHD Detection from fMRI Dataset
Anjan Chowdhury, Rajdeep Chatterjee, Geetanjali Aich, et al.
Lecture notes in computer science (2024), pp. 137-147
Closed Access | Times Cited: 3
The utility of wearable electroencephalography combined with behavioral measures to establish a practical multi-domain model for facilitating the diagnosis of young children with attention-deficit/hyperactivity disorder
I‐Chun Chen, Che‐Lun Chang, Meng‐Han Chang, et al.
Journal of Neurodevelopmental Disorders (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3
COMPLEXITY AND MEMORY-BASED COMPARISON OF THE BRAIN ACTIVITY BETWEEN ADHD AND HEALTHY SUBJECTS WHILE PLAYING A SERIOUS GAME
Norazryana Mat Dawi, Kamil Kuča, Ondřej Krejcar, et al.
Fractals (2021) Vol. 29, Iss. 05, pp. 2150202-2150202
Open Access | Times Cited: 21
Artificial Intelligence Based Techniques for the Detection of Socio-Behavioral Disorders: A Systematic Review
Mehak Mengi, Deepti Malhotra
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 5, pp. 2811-2855
Closed Access | Times Cited: 20
Treatments and regulatory mechanisms of acoustic stimuli on mood disorders and neurological diseases
Yi‐Kai Chen, Julianne Sun, Junxian Tao, et al.
Frontiers in Neuroscience (2024) Vol. 17
Open Access | Times Cited: 2
A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis
Nasser Ali Aljarallah, Ashit Kumar Dutta, Abdul Rahaman Wahab Sait
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 12, pp. 6422-6422
Open Access | Times Cited: 2
Advances in the etiology and neuroimaging of children with attention deficit hyperactivity disorder
Fang Shen, Hui Zhou
Frontiers in Pediatrics (2024) Vol. 12
Open Access | Times Cited: 2
Machine Learning Prediction of ADHD Severity: Association and Linkage to ADGRL3, DRD4, and SNAP25
Martha L. Cervantes-Henríquez, Johan E. Acosta-López, Ariel F. Martinez, et al.
Journal of Attention Disorders (2021) Vol. 26, Iss. 4, pp. 587-605
Closed Access | Times Cited: 16
A Novel Knowledge Distillation-Based Feature Selection for the Classification of ADHD
Naseer Ahmed Khan, Samer Abdulateef Waheeb, Atif Riaz, et al.
Biomolecules (2021) Vol. 11, Iss. 8, pp. 1093-1093
Open Access | Times Cited: 16
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