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For: Bhat S, Acharya UR, Hagiwara Y, Dadmehr N, Adeli H. Parkinson's disease: Cause factors, measurable indicators, and early diagnosis. Comput Biol Med 2018;102:234-41. [PMID: 30253869 DOI: 10.1016/j.compbiomed.2018.09.008] [Cited by in Crossref: 44] [Cited by in F6Publishing: 58] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
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4 Li Z, Yang J, Wang Y, Cai M, Liu X, Lu K. Early diagnosis of Parkinson's disease using Continuous Convolution Network: Handwriting recognition based on off-line hand drawing without template. Journal of Biomedical Informatics 2022;130:104085. [DOI: 10.1016/j.jbi.2022.104085] [Reference Citation Analysis]
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6 Aljalal M, Aldosari SA, Alsharabi K, Abdurraqeeb AM, Alturki FA. Parkinson’s Disease Detection from Resting-State EEG Signals Using Common Spatial Pattern, Entropy, and Machine Learning Techniques. Diagnostics 2022;12:1033. [DOI: 10.3390/diagnostics12051033] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
7 Ya Y, Ji L, Jia Y, Zou N, Jiang Z, Yin H, Mao C, Luo W, Wang E, Fan G. Machine Learning Models for Diagnosis of Parkinson’s Disease Using Multiple Structural Magnetic Resonance Imaging Features. Front Aging Neurosci 2022;14:808520. [DOI: 10.3389/fnagi.2022.808520] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Suri JS, Paul S, Maindarkar MA, Puvvula A, Saxena S, Saba L, Turk M, Laird JR, Khanna NN, Viskovic K, Singh IM, Kalra M, Krishnan PR, Johri A, Paraskevas KI. Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review. Metabolites 2022;12:312. [DOI: 10.3390/metabo12040312] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
9 Stępień P, Kawa J, Sitek EJ, Wieczorek D, Sikorski R, Dąbrowska M, Sławek J, Pietka E. Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson's Disease. Sensors (Basel) 2022;22:1688. [PMID: 35214587 DOI: 10.3390/s22041688] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Hassin-Baer S, Cohen OS, Israeli-Korn S, Yahalom G, Benizri S, Sand D, Issachar G, Geva AB, Shani-Hershkovich R, Peremen Z. Identification of an early-stage Parkinson's disease neuromarker using event-related potentials, brain network analytics and machine-learning. PLoS One 2022;17:e0261947. [PMID: 34995285 DOI: 10.1371/journal.pone.0261947] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Kour N, Gupta S, Arora S. A vision‐based clinical analysis for classification of knee osteoarthritis, Parkinson's disease and normal gait with severity based on k‐nearest neighbour. Expert Systems. [DOI: 10.1111/exsy.12955] [Reference Citation Analysis]
12 Pramanik M, Pradhan R, Nandy P, Bhoi AK, Barsocchi P. The ForEx++ based decision tree ensemble approach for robust detection of Parkinson’s disease. J Ambient Intell Human Comput. [DOI: 10.1007/s12652-022-03719-x] [Reference Citation Analysis]
13 Lamba R, Gulati T, Jain A. A Hybrid Feature Selection Approach for Parkinson’s Detection Based on Mutual Information Gain and Recursive Feature Elimination. Arab J Sci Eng. [DOI: 10.1007/s13369-021-06544-0] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
14 Abdul Gafoor SH, Theagarajan P. Intelligent approach of score-based artificial fish swarm algorithm (SAFSA) for Parkinson's disease diagnosis. IJICC 2022;ahead-of-print. [DOI: 10.1108/ijicc-10-2021-0226] [Reference Citation Analysis]
15 Paul S, Maindarkar M, Saxena S, Saba L, Turk M, Kalra M, Krishnan PR, Suri JS. Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson's Disease: A Narrative Review. Diagnostics (Basel) 2022;12:166. [PMID: 35054333 DOI: 10.3390/diagnostics12010166] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 10.0] [Reference Citation Analysis]
16 Jacob L, Smith L, Koyanagi A, Schnitzler A, Il Shin J, Kostev K. Association between osteoarthritis and the incidence of Parkinson's disease in the United Kingdom. Clin Park Relat Disord 2021;5:100120. [PMID: 34888519 DOI: 10.1016/j.prdoa.2021.100120] [Reference Citation Analysis]
17 Vidya B, P S. Gait based Parkinson’s disease diagnosis and severity rating using multi-class support vector machine. Applied Soft Computing 2021;113:107939. [DOI: 10.1016/j.asoc.2021.107939] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Patel K, Mistry C, Mehta D, Thakker U, Tanwar S, Gupta R, Kumar N. A survey on artificial intelligence techniques for chronic diseases: open issues and challenges. Artif Intell Rev. [DOI: 10.1007/s10462-021-10084-2] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
19 Dumitrescu C, Costea IM, Cormos AC, Semenescu A. Automatic Detection of K-Complexes Using the Cohen Class Recursiveness and Reallocation Method and Deep Neural Networks with EEG Signals. Sensors (Basel) 2021;21:7230. [PMID: 34770537 DOI: 10.3390/s21217230] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
20 Loh HW, Hong W, Ooi CP, Chakraborty S, Barua PD, Deo RC, Soar J, Palmer EE, Acharya UR. Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021). Sensors (Basel) 2021;21:7034. [PMID: 34770340 DOI: 10.3390/s21217034] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
21 Saçmacı H, Erkoç MF, Aktürk T. Measurement of the facial nerve thickness and its correlation with freezing phenomenon and hypomimia in Parkinson's disease. Clin Neurol Neurosurg 2021;210:106960. [PMID: 34571338 DOI: 10.1016/j.clineuro.2021.106960] [Reference Citation Analysis]
22 Barua PD, Dogan S, Tuncer T, Baygin M, Acharya UR. Novel automated PD detection system using aspirin pattern with EEG signals. Comput Biol Med 2021;137:104841. [PMID: 34509880 DOI: 10.1016/j.compbiomed.2021.104841] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
23 Wang S, Wen Q, Xiong B, Zhang L, Yu X, Ouyang X. Long Noncoding RNA NEAT1 Knockdown Ameliorates 1-Methyl-4-Phenylpyridine-Induced Cell Injury Through MicroRNA-519a-3p/SP1 Axis in Parkinson Disease. World Neurosurg 2021;156:e93-e103. [PMID: 34508910 DOI: 10.1016/j.wneu.2021.08.147] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
24 Bollipo LM, K V K. Fast and robust supervised machine learning approach for classification and prediction of Parkinson’s disease onset. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2021;9:690-706. [DOI: 10.1080/21681163.2021.1941262] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Loh HW, Ooi CP, Palmer E, Barua PD, Dogan S, Tuncer T, Baygin M, Acharya UR. GaborPDNet: Gabor Transformation and Deep Neural Network for Parkinson’s Disease Detection Using EEG Signals. Electronics 2021;10:1740. [DOI: 10.3390/electronics10141740] [Cited by in Crossref: 2] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
26 Hoq M, Uddin MN, Park SB. Vocal Feature Extraction-Based Artificial Intelligent Model for Parkinson's Disease Detection. Diagnostics (Basel) 2021;11:1076. [PMID: 34208330 DOI: 10.3390/diagnostics11061076] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
27 Kaur I, Behl T, Sehgal A, Singh S, Sharma N, Aleya L, Bungau S. Connecting the dots between mitochondrial dysfunction and Parkinson's disorder: focus mitochondria-targeting therapeutic paradigm in mitigating the disease severity. Environ Sci Pollut Res Int 2021;28:37060-81. [PMID: 34053042 DOI: 10.1007/s11356-021-14619-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
28 Yao NT, Zheng Q, Xu ZQ, Yin JH, Lu LG, Zuo Q, Yang S, Zhang CL, Jiao L. Positron emission computed tomography/single photon emission computed tomography in Parkinson disease. Chin Med J (Engl) 2020;133:1448-55. [PMID: 32404694 DOI: 10.1097/CM9.0000000000000836] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
29 Scharfenort M, Timpka J, Sahlström T, Henriksen T, Nyholm D, Odin P. Close relationships in Parkinson´s disease patients with device-aided therapy. Brain Behav 2021;11:e02102. [PMID: 33949144 DOI: 10.1002/brb3.2102] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
30 Tong Y, Liu J. Review of Research and Development of Supernumerary Robotic Limbs. IEEE/CAA J Autom Sinica 2021;8:929-52. [DOI: 10.1109/jas.2021.1003961] [Cited by in Crossref: 12] [Cited by in F6Publishing: 2] [Article Influence: 12.0] [Reference Citation Analysis]
31 Kobiec T, Otero-Losada M, Chevalier G, Udovin L, Bordet S, Menéndez-Maissonave C, Capani F, Pérez-Lloret S. The Renin-Angiotensin System Modulates Dopaminergic Neurotransmission: A New Player on the Scene. Front Synaptic Neurosci 2021;13:638519. [PMID: 33967734 DOI: 10.3389/fnsyn.2021.638519] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
32 Diaz M, Moetesum M, Siddiqi I, Vessio G. Sequence-based dynamic handwriting analysis for Parkinson’s disease detection with one-dimensional convolutions and BiGRUs. Expert Systems with Applications 2021;168:114405. [DOI: 10.1016/j.eswa.2020.114405] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 7.0] [Reference Citation Analysis]
33 Khare SK, Bajaj V, Acharya UR. Detection of Parkinson’s disease using automated tunable Q wavelet transform technique with EEG signals. Biocybernetics and Biomedical Engineering 2021;41:679-89. [DOI: 10.1016/j.bbe.2021.04.008] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
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35 Pei X, Fan H, Tang Y. Temporal pyramid attention‐based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data. IET signal process 2021;15:80-7. [DOI: 10.1049/sil2.12018] [Reference Citation Analysis]
36 Wang Q, Wang H, Hu F, Hua C, Wang D. Using convolutional neural networks to decode EEG-based functional brain network with different severity of acrophobia. J Neural Eng 2021;18:016007. [DOI: 10.1088/1741-2552/abcdbd] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Zhou Q, Zhang MM, Liu M, Tan ZG, Qin QL, Jiang YG. LncRNA XIST sponges miR-199a-3p to modulate the Sp1/LRRK2 signal pathway to accelerate Parkinson's disease progression. Aging (Albany NY) 2021;13:4115-37. [PMID: 33494069 DOI: 10.18632/aging.202378] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
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39 De Cola MC, Triglia G, Camera M, Corallo F, Di Cara M, Bramanti P, Lo Buono V. Effect of neurological screening on early dementia detection in southern Italy. J Int Med Res 2020;48:300060520949763. [PMID: 33081552 DOI: 10.1177/0300060520949763] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]
40 Gómez-Rodellar A, Palacios-Alonso D, Ferrández Vicente JM, Mekyska J, Álvarez-Marquina A, Gómez-Vilda P. A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis. Int J Neural Syst 2020;30:2050058. [PMID: 32880202 DOI: 10.1142/S0129065720500586] [Reference Citation Analysis]
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44 Vuttipittayamongkol P, Elyan E. Improved Overlap-based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson’s Disease. Int J Neur Syst 2020;30:2050043. [DOI: 10.1142/s0129065720500434] [Cited by in Crossref: 7] [Cited by in F6Publishing: 14] [Article Influence: 3.5] [Reference Citation Analysis]
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