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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 can detect the presence of Mild cognitive impairment in patients affected by Parkinson’s Disease
Carlo Ricciardi, Marianna Amboni, Chiara De Santis, et al.
2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) (2020), pp. 1-6
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters
Marta Isabel A.S.N Ferreira, Fábio Augusto Barbieri, Vinícius Christianini Moreno, et al.
Gait & Posture (2022) Vol. 98, pp. 49-55
Open Access | Times Cited: 45
Identification of a Gait Pattern for Detecting Mild Cognitive Impairment in Parkinson’s Disease
Michela Russo, Marianna Amboni, Paolo Barone, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 1985-1985
Open Access | Times Cited: 18
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
Kinematic and Kinetic Gait Features Associated With Mild Cognitive Impairment in Parkinson’s Disease
Michela Russo, Marianna Amboni, Antonio Volzone, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 2676-2687
Open Access | Times Cited: 4
Gait analysis may distinguish progressive supranuclear palsy and Parkinson disease since the earliest stages
Marianna Amboni, Carlo Ricciardi, Marina Picillo, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 23
Extracting Features from Poincaré Plots to Distinguish Congestive Heart Failure Patients According to NYHA Classes
Giovanni D’Addio, Leandro Donisi, Giuseppe Cesarelli, et al.
Bioengineering (2021) Vol. 8, Iss. 10, pp. 138-138
Open Access | Times Cited: 20
Mild Cognitive Impairment Subtypes Are Associated With Peculiar Gait Patterns in Parkinson’s Disease
Marianna Amboni, Carlo Ricciardi, Sofia Cuoco, et al.
Frontiers in Aging Neuroscience (2022) Vol. 14
Open Access | Times Cited: 14
Machine learning can predict mild cognitive impairment in Parkinson's disease
Marianna Amboni, Carlo Ricciardi, Sarah Adamo, et al.
Frontiers in Neurology (2022) Vol. 13
Open Access | Times Cited: 14
Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
Alfonso Maria Ponsiglione, Carlo Ricciardi, Francesco Amato, et al.
Sensors (2022) Vol. 22, Iss. 5, pp. 1708-1708
Open Access | Times Cited: 12
Parkinson's Disease Detection Using Machine Learning
M. S. Roobini, Yaragundla Rajesh Kumar Reddy, Udayagiri Sushmanth Girish Royal, et al.
2022 International Conference on Communication, Computing and Internet of Things (IC3IoT) (2022)
Closed Access | Times Cited: 11
Gait Analysis in Progressive Supranuclear Palsy Phenotypes
Marina Picillo, Carlo Ricciardi, Maria Francesca Tepedino, et al.
Frontiers in Neurology (2021) Vol. 12
Open Access | Times Cited: 15
PPGCN: Phase-Aligned Periodic Graph Convolutional Network for Dual-Task-Based Cognitive Impairment Detection
Ákos Godó, Shuqiong Wu, Fumio Okura, et al.
IEEE Access (2024) Vol. 12, pp. 37679-37691
Open Access | Times Cited: 1
Interplay between gait and neuropsychiatric symptoms in Parkinson’s Disease
Michela Russo, Marianna Amboni, Antonio Volzone, et al.
European Journal of Translational Myology (2022) Vol. 32, Iss. 2
Open Access | Times Cited: 7
Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations
Annalisa Vitale, Rossella Villa, Lorenzo Ugga, et al.
Mathematical Biosciences & Engineering (2021) Vol. 18, Iss. 2, pp. 1753-1773
Open Access | Times Cited: 9
Machine learning analysis: general features, requirements and cardiovascular applications
Carlo Ricciardi, Renato Cuocolo, Rosario Megna, et al.
Minerva Cardiology and Angiology (2021) Vol. 70, Iss. 1
Closed Access | Times Cited: 6
Agreement between Optoelectronic System and Wearable Sensors for the Evaluation of Gait Spatiotemporal Parameters in Progressive Supranuclear Palsy
Carlo Ricciardi, Noemi Pisani, Leandro Donisi, et al.
Sensors (2023) Vol. 23, Iss. 24, pp. 9859-9859
Open Access | Times Cited: 2
A Cluster Analysis for Parkinson's Disease Phenotyping with Gait Parameters
Michela Russo, Carlo Ricciardi, Marianna Amboni, et al.
2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (2023), pp. 882-887
Closed Access | Times Cited: 2
Resolution Resampling of Ultrasound Images in Placenta Previa Patients: Influence on Radiomics Data Reliability and Usefulness for Machine Learning
Carlo Ricciardi, Renato Cuocolo, Francesco Verde, et al.
IFMBE proceedings (2020), pp. 1011-1018
Closed Access | Times Cited: 5
A Health Technology Assessment in Maxillofacial Cancer Surgery by Using the Six Sigma Methodology
Carlo Ricciardi, Giovanni Dell’Aversana Orabona, Ilaria Picone, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 18, pp. 9846-9846
Open Access | Times Cited: 4
Early Detection of Parkinson Disease Throughbiomedical Speech and Voice Analysis
Pawan Kumar Badhan, Manjeet Kaur
International Journal on Soft Computing Artificial Intelligence and Applications (2024) Vol. 13, Iss. 1, pp. 11-22
Open Access
Automatic Diagnosis of Parkinson’s Disease using Handwriting Patterns
T. Nagamani
Deleted Journal (2024) Vol. 20, Iss. 7s, pp. 1395-1405
Open Access
Innovative Deep Learning Approach for Parkinson's Disease Prediction: Leveraging Convolutional Neural Networks for Early Detection
Bhagyashri R. Wankar, Nikita V. Kshirsagar, A Jadhav, et al.
EAI Endorsed Transactions on Pervasive Health and Technology (2024) Vol. 10
Open Access
Early Detection of Parkinson Disease through Biomedical Analysis
Pawan Kumar Badhan, Manjeet Kaur
SSRN Electronic Journal (2024)
Closed Access
Evaluation Method of Cognitive Level Based on Machine Learning and Wearable Device
Shuai Tao, Hongbin Hu, Jie Zhao, et al.
Lecture notes in electrical engineering (2024), pp. 143-150
Closed Access
A QUALITATIVE AND QUANTITATIVE APPROACH USING MACHINE LEARNING AND NON-MOTOR SYMPTOMS FOR PARKINSON’S DISEASE CLASSIFICATION. A HIERARCHICAL STUDY
Anitha Rani Palakayala, P. Kuppusamy
Applied Computer Science (2024) Vol. 20, Iss. 3, pp. 171-191
Open Access
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