Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach
Masoud Abdollahi, Sajad Ashouri, Mohsen Abedi, et al.
Sensors (2020) Vol. 20, Iss. 12, pp. 3600-3600
Open Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

Artificial Intelligence and Computer Aided Diagnosis in Chronic Low Back Pain: A Systematic Review
Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 10, pp. 5971-5971
Open Access | Times Cited: 44
Technologies in Home-Based Digital Rehabilitation: Scoping Review
A.R. Arntz, F. Parkes Weber, Marietta Handgraaf, et al.
JMIR Rehabilitation and Assistive Technologies (2023) Vol. 10, pp. e43615-e43615
Open Access | Times Cited: 32
Fall Risk Assessment in Stroke Survivors: A Machine Learning Model Using Detailed Motion Data from Common Clinical Tests and Motor-Cognitive Dual-Tasking
Masoud Abdollahi, Ehsan Rashedi, Sonia Jahangiri, et al.
Sensors (2024) Vol. 24, Iss. 3, pp. 812-812
Open Access | Times Cited: 13
Applications of Artificial Intelligence in Pain Medicine
Alaa Abd‐Elsayed, Christopher L. Robinson, Zwade Marshall, et al.
Current Pain and Headache Reports (2024) Vol. 28, Iss. 4, pp. 229-238
Closed Access | Times Cited: 10
Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain
Doaa A. Abdel Hady, Tarek Abd El‐Hafeez
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Wearable devices may aid the recognition of fluctuation-related pain in Parkinson’s disease—An exploratory, cross-sectional analysis of two prospective observational studies
Katarina Rukavina, Juliet Staunton, Pavlos Zinzalias, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0316563-e0316563
Open Access | Times Cited: 1
Machine Learning in Pain Medicine: An Up-To-Date Systematic Review
Maria Matsangidou, Andreas Liampas, Melpo Pittara, et al.
Pain and Therapy (2021) Vol. 10, Iss. 2, pp. 1067-1084
Open Access | Times Cited: 45
Sensor Fusion and Machine Learning for Seated Movement Detection With Trunk Orthosis
Ahmad Zahid Rao, Saba Shahid Siddique, Muhammad Danish Mujib, et al.
IEEE Access (2024) Vol. 12, pp. 41676-41687
Open Access | Times Cited: 7
Smartphone-based human fatigue level detection using machine learning approaches
Swapnali Karvekar, Masoud Abdollahi, Ehsan Rashedi
Ergonomics (2021) Vol. 64, Iss. 5, pp. 600-612
Closed Access | Times Cited: 36
The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review
Joseph Okeibunor, Anelisa Jaca, Chinwe Juliana Iwu, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 15
A Comprehensive Review of AI-Based Low Back Pain Assessment and Rehabilitation
Manvendra Singh, Chandan Kumar, Md. Sarfaraj Alam Ansari, et al.
Communications in computer and information science (2025), pp. 174-181
Closed Access
Integrating multidimensional data analytics for precision diagnosis of chronic low back pain
Sam Vickery, Frederic Junker, Rebekka Döding, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review
Théo Jourdan, Noëlie Debs, Carole Frindel
Sensors (2021) Vol. 21, Iss. 14, pp. 4808-4808
Open Access | Times Cited: 31
IMU-Based Monitoring for Assistive Diagnosis and Management of IoHT: A Review
Fan Bo, Mustafa Ozkan Yerebakan, Yanning Dai, et al.
Healthcare (2022) Vol. 10, Iss. 7, pp. 1210-1210
Open Access | Times Cited: 21
Classification of the Pathological Range of Motion in Low Back Pain Using Wearable Sensors and Machine Learning
Fernando Villalba-Meneses, César Guevara, Alejandro B. Lojan, et al.
Sensors (2024) Vol. 24, Iss. 3, pp. 831-831
Open Access | Times Cited: 4
Exploring the Real-Time Variability and Complexity of Sitting Patterns in Office Workers with Non-Specific Chronic Spinal Pain and Pain-Free Individuals
Eduarda Oliosi, Afonso Caetano Júlio, Phillip Probst, et al.
Sensors (2024) Vol. 24, Iss. 14, pp. 4750-4750
Open Access | Times Cited: 3
AI-driven Diagnostic Processes and Comprehensive Multimodal Models in Pain Medicine
Marco Cascella, Marco L.G. Leoni, Mohammed Naveed Shariff, et al.
(2024)
Open Access | Times Cited: 3
Artificial Intelligence-Driven Diagnostic Processes and Comprehensive Multimodal Models in Pain Medicine
Marco Cascella, Matteo Luigi Giuseppe Leoni, Mohammed Naveed Shariff, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 9, pp. 983-983
Open Access | Times Cited: 3
Kinematic Analysis of 360° Turning in Stroke Survivors Using Wearable Motion Sensors
Masoud Abdollahi, Pranav Madhav Kuber, Michael Shiraishi, et al.
Sensors (2022) Vol. 22, Iss. 1, pp. 385-385
Open Access | Times Cited: 15
Role of Artificial Intelligence and Machine Learning in the prediction of the pain: A scoping systematic review
Ravi Sankaran, Anand Kumar, Harilal Parasuram
Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine (2022) Vol. 236, Iss. 10, pp. 1478-1491
Closed Access | Times Cited: 12
Artificial intelligence: a new cutting-edge tool in spine surgery
Guna Pratheep Kalanjiyam, T. Chandramohan, M J Shankar Raman, et al.
Asian Spine Journal (2024) Vol. 18, Iss. 3, pp. 458-471
Open Access | Times Cited: 2
Machine Learning Identifies Chronic Low Back Pain Patients from an Instrumented Trunk Bending and Return Test
P.S. Thiry, Martin Houry, Laurent Philippe, et al.
Sensors (2022) Vol. 22, Iss. 13, pp. 5027-5027
Open Access | Times Cited: 10
Decoding Wilson disease: a machine learning approach to predict neurological symptoms
Yulong Yang, Gang-Ao Wang, Shuzhen Fang, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 1
Comparative analysis of machine learning models for efficient low back pain prediction using demographic and lifestyle factors
Junhee Kim
Journal of Back and Musculoskeletal Rehabilitation (2024) Vol. 37, Iss. 6, pp. 1631-1640
Open Access | Times Cited: 1
A Practical Sensor-Based Methodology for the Quantitative Assessment and Classification of Chronic Non Specific Low Back Patients (NSLBP) in Clinical Settings
Mehrdad Davoudi, Seyed Mohammadreza Shokouhyan, Mohsen Abedi, et al.
Sensors (2020) Vol. 20, Iss. 10, pp. 2902-2902
Open Access | Times Cited: 11
Page 1 - Next Page

Scroll to top