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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:

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis
Y. Iwamoto, Takeshi Imura, Ryo Tanaka, et al.
Journal of Stroke and Cerebrovascular Diseases (2020) Vol. 29, Iss. 12, pp. 105332-105332
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Machine Learning in Action: Stroke Diagnosis and Outcome Prediction
Shraddha Mainali, Marin E. Darsie, Keaton S. Smetana
Frontiers in Neurology (2021) Vol. 12
Open Access | Times Cited: 93
Evaluation of Rehabilitation Outcomes in Patients with Chronic Neurological Health Conditions Using a Machine Learning Approach
Gabriele Santilli, Massimiliano Mangone, Francesco Agostini, et al.
Journal of Functional Morphology and Kinesiology (2024) Vol. 9, Iss. 4, pp. 176-176
Open Access | Times Cited: 7
Upper Limb Rehabilitation System for Stroke Survivors Based on Multi-Modal Sensors and Machine Learning
Sheng Miao, Shen Chen, Xiaochen Feng, et al.
IEEE Access (2021) Vol. 9, pp. 30283-30291
Open Access | Times Cited: 38
Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator–Optimized Stacking Ensemble Approaches
Pei-Hua Lin, Ping‐Huan Kuo, Kuan-Lin Chen
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 5, pp. 2745-2758
Closed Access | Times Cited: 5
Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach
Eloise de Oliveira Lima, José Maurício Ramos de Souza Neto, Francisco Enrique Vicente Castro, et al.
Brain Topography (2025) Vol. 38, Iss. 2
Closed Access
Smart sensor-based activity recognition for patients in healthcare
Nazgol Gharsi, Mohammadi Kamyar, Mohammad Shahbazi
Elsevier eBooks (2025), pp. 479-502
Closed Access
Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients
Jeffrey R. Vitt, Shraddha Mainali
Seminars in Neurology (2024) Vol. 44, Iss. 03, pp. 342-356
Closed Access | Times Cited: 4
Prognostic Factors in Neurorehabilitation of Stroke: A Comparison among Regression, Neural Network, and Cluster Analyses
Marco Iosa, Giovanni Morone, Gabriella Antonucci, et al.
Brain Sciences (2021) Vol. 11, Iss. 9, pp. 1147-1147
Open Access | Times Cited: 24
The Comparison and Interpretation of Machine-Learning Models in Post-Stroke Functional Outcome Prediction
Shih-Chieh Chang, Chan‐Lin Chu, Chih‐Kuang Chen, et al.
Diagnostics (2021) Vol. 11, Iss. 10, pp. 1784-1784
Open Access | Times Cited: 21
A Deep Learning-Based Upper Limb Rehabilitation Exercise Status Identification System
Binoy B. Nair, N.R. Sakthivel
Arabian Journal for Science and Engineering (2022) Vol. 48, Iss. 2, pp. 1237-1271
Closed Access | Times Cited: 9
Application of an Artificial Neural Network to Identify the Factors Influencing Neurorehabilitation Outcomes of Patients with Ischemic Stroke Treated with Thrombolysis
Marco Iosa, Stefano Paolucci, Gabriella Antonucci, et al.
Biomolecules (2023) Vol. 13, Iss. 2, pp. 334-334
Open Access | Times Cited: 5
Clinical Prediction Rule for Identifying the Stroke Patients who will Obtain Clinically Important Improvement of Upper Limb Motor Function by Robot-Assisted Upper Limb
Y. Iwamoto, Takeshi Imura, Ryo Tanaka, et al.
Journal of Stroke and Cerebrovascular Diseases (2022) Vol. 31, Iss. 7, pp. 106517-106517
Closed Access | Times Cited: 8
Clinical Features for Identifying the Possibility of Toileting Independence after Convalescent Inpatient Rehabilitation in Severe Stroke Patients: A Decision Tree Analysis Based on a Nationwide Japan Rehabilitation Database
Takeshi Imura, Yu Inoue, Ryo Tanaka, et al.
Journal of Stroke and Cerebrovascular Diseases (2020) Vol. 30, Iss. 2, pp. 105483-105483
Closed Access | Times Cited: 9
Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis
Takeshi Imura, Haruki Toda, Y. Iwamoto, et al.
Journal of Stroke and Cerebrovascular Diseases (2021) Vol. 30, Iss. 10, pp. 106011-106011
Closed Access | Times Cited: 9
Early Initiation of Exoskeletal Robotic Gait Training Improves Functional Outcomes in the Patients with Stroke: A Retrospective Observational Study
Akira Degami, Shingo Taki, Takeshi Imura, et al.
European Neurology (2022) Vol. 86, Iss. 2, pp. 121-127
Closed Access | Times Cited: 6
A model for predicting physical function upon discharge of hospitalized older adults in Taiwan—a machine learning approach based on both electronic health records and comprehensive geriatric assessment
Wei‐Min Chu, Yu‐Tse Tsan, Peiyu Chen, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 3
Development of a clinical prediction rule for patients with cervical spinal cord injury who have difficulty in obtaining independent living
Tomonari Hori, Takeshi Imura, Ryo Tanaka
The Spine Journal (2021) Vol. 22, Iss. 2, pp. 321-328
Closed Access | Times Cited: 6
A Simplified Clinical Prediction Rule for Prognosticating Dependent Daily Living in Patients with Thoracic Spinal Cord Injury: A Multicenter Nationwide Japan Registry Study
Takeshi Imura, Tomonari Hori, Ryou Tanaka
European Neurology (2023) Vol. 86, Iss. 3, pp. 178-184
Closed Access | Times Cited: 2
A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 2—Data From Nonwearables
Woojung Lee, Naomi Schwartz, Aasthaa Bansal, et al.
Value in Health (2022) Vol. 25, Iss. 12, pp. 2053-2061
Closed Access | Times Cited: 4
Discharge Rehabilitation Measures Predict Activity Limitations in Patients With Stroke 6 Months After Inpatient Rehabilitation
Maria Minor, Abhishek Jaywant, Joan Toglia, et al.
American Journal of Physical Medicine & Rehabilitation (2021) Vol. 101, Iss. 8, pp. 761-767
Closed Access | Times Cited: 5
Palliative Care for Older Adults Hospitalized for Stroke From the Informal Caregivers' Perspectives
Jing Jing Su, Rose S.Y. Lin, Jenniffer Torralba Paguio, et al.
The Journal of Cardiovascular Nursing (2022) Vol. 38, Iss. 3, pp. E110-E119
Open Access | Times Cited: 3
A Scoping Review of Prognosis Prediction Studies Focusing on Activity and Participation Among Patients with Stroke in Japan
Ryu Kobayashi, S. Maruyama, Takuya Hirose, et al.
Asian Journal of Occupational Therapy (2024) Vol. 20, Iss. 1, pp. 29-48
Open Access
Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge
Takeshi Imura, Y. Iwamoto, Yuki Azuma, et al.
Journal of Stroke and Cerebrovascular Diseases (2021) Vol. 30, Iss. 8, pp. 105868-105868
Closed Access | Times Cited: 3
Interventions focusing on learning pre-transfer wheelchair manipulation in a patient with severe Alzheimer’s disease: a case report
Keita Nakagawa, Shusaku Kanai, Sosuke Kitakaze, et al.
Physiotherapy Theory and Practice (2022) Vol. 40, Iss. 5, pp. 1091-1099
Closed Access | Times Cited: 1
Essential information for neurorecovery clinical trial design: trajectory of global disability in first 90 days post-stroke in patients discharged to acute rehabilitation facilities
Shayandokht Taleb, Jenny Ji-hyun Lee, Pamela W. Duncan, et al.
BMC Neurology (2023) Vol. 23, Iss. 1
Open Access
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