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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:

Accuracy of Machine Learning Using the Montreal Cognitive Assessment for the Diagnosis of Cognitive Impairment in Parkinson’s Disease
Junbeom Jeon, Ki-Yong Kim, Kyeongmin Baek, et al.
Journal of Movement Disorders (2022) Vol. 15, Iss. 2, pp. 132-139
Open Access | Times Cited: 10

Showing 10 citing articles:

Machine learning for the detection and diagnosis of cognitive impairment in Parkinson’s Disease: A systematic review
Callum Altham, Huaizhong Zhang, Ella Pereira
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0303644-e0303644
Open Access | Times Cited: 7
Are the criteria for PD-MCI diagnosis comprehensive? A Machine Learning study with modified criteria
Chiara Longo, Daniele Romano, Maria Pennacchio, et al.
Parkinsonism & Related Disorders (2024) Vol. 124, pp. 106987-106987
Closed Access | Times Cited: 6
One-year practice effects predict long-term cognitive outcomes in Parkinson's disease
Salvador Pérez, Vincent Koppelmans, Kevin Duff, et al.
Journal of Parkinson s Disease (2025)
Open Access
Construction of a prediction and visualization system for cognitive impairment in elderly COPD patients based on self-assigning feature weights and residual evolution model
Wenwen Cheng, Yù Chen, Xiaohui Liu
Frontiers in Artificial Intelligence (2025) Vol. 8
Open Access
Vascular and glymphatic dysfunction as drivers of cognitive impairment in Alzheimer's disease: Insights from computational approaches
Gehan Fatima, Akm Ashiquzzaman, Sang Seong Kim, et al.
Neurobiology of Disease (2025), pp. 106877-106877
Open Access
Decoding Parkinson's disease: A multifaceted approach to diagnosis and biomarker discovery
Mahmoud Ragab, Al-Hassan Soliman Wadan, Azza Shaltout, et al.
Elsevier eBooks (2024), pp. 235-256
Closed Access | Times Cited: 1
Predictive value of machine learning in diagnosing cognitive impairment in patients with Parkinson’s disease: a systematic review and meta-analysis
Menghan Sun, Ting Yan, Ruijun Liu, et al.
Annals of Palliative Medicine (2022) Vol. 11, Iss. 12, pp. 3775-3784
Open Access | Times Cited: 5
Comparing Montreal Cognitive Assessment Performance in Parkinson’s Disease Patients: Age- and Education-Adjusted Cutoffs vs. Machine Learning
Kyeongmin Baek, Young Min Kim, Han Kyu Na, et al.
Journal of Movement Disorders (2024) Vol. 17, Iss. 2, pp. 171-180
Open Access
Comparative Study of ML Methods for Predictive Analysis of Depression Onset
Naga Raju` Kanchapogu, Sachi Nandan Mohanty
(2024), pp. 193-198
Closed Access
MRI quantified perivascular space metrics as imaging biomarkers for assessing the severity of cognitive impairment and sleep disturbance in young adults with long-time mobile phone use through machine learning approaches
Li M. Li, Jiaojiao Wu, Bin Li, et al.
Research Square (Research Square) (2024)
Closed Access
Diagnosis of PD-MCI Using Machine Learning: Comparing the Sensitivity of Different Level of Cognitive Assessment
Chiara Longo, Daniele Romano, Maria Pennacchio, et al.
(2023)
Closed Access
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