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Monteiro F, Carvalho Ó, Sousa N, Silva FS, Sotiropoulos I. Photobiomodulation and visual stimulation against cognitive decline and Alzheimer's disease pathology: A systematic review. ALZHEIMER'S & DEMENTIA: TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2022; 8:e12249. [DOI: 10.1002/trc2.12249] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 12/01/2021] [Accepted: 12/15/2021] [Indexed: 11/27/2022]
Affiliation(s)
- Francisca Monteiro
- Center for Microelectromechanical Systems (CMEMS) Campus Azurém University of Minho Guimarães Portugal
- ICVS/3B's ‐ PT Government Associate Laboratory Braga/Guimarães Portugal
- LABBELS—Associate Laboratory University of Minho Guimarães Portugal
| | - Óscar Carvalho
- Center for Microelectromechanical Systems (CMEMS) Campus Azurém University of Minho Guimarães Portugal
- LABBELS—Associate Laboratory University of Minho Guimarães Portugal
| | - Nuno Sousa
- ICVS/3B's ‐ PT Government Associate Laboratory Braga/Guimarães Portugal
- Life and Health Sciences Research Institute (ICVS) School of Medicine University of Minho Campus de Gualtar Braga Portugal
| | - Filipe S. Silva
- Center for Microelectromechanical Systems (CMEMS) Campus Azurém University of Minho Guimarães Portugal
- LABBELS—Associate Laboratory University of Minho Guimarães Portugal
| | - Ioannis Sotiropoulos
- ICVS/3B's ‐ PT Government Associate Laboratory Braga/Guimarães Portugal
- Life and Health Sciences Research Institute (ICVS) School of Medicine University of Minho Campus de Gualtar Braga Portugal
- Institute of Biosciences and Applications NCSR Demokritos Athens Greece
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Tanveer M, Richhariya B, Khan RU, Rashid AH, Khanna P, Prasad M, Lin CT. Machine Learning Techniques for the Diagnosis of Alzheimer’s Disease. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING, COMMUNICATIONS, AND APPLICATIONS 2020; 16:1-35. [DOI: 10.1145/3344998] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 07/01/2019] [Indexed: 08/30/2023]
Abstract
Alzheimer’s disease is an incurable neurodegenerative disease primarily affecting the elderly population. Efficient automated techniques are needed for early diagnosis of Alzheimer’s. Many novel approaches are proposed by researchers for classification of Alzheimer’s disease. However, to develop more efficient learning techniques, better understanding of the work done on Alzheimer’s is needed. Here, we provide a review on 165 papers from 2005 to 2019, using various feature extraction and machine learning techniques. The machine learning techniques are surveyed under three main categories: support vector machine (SVM), artificial neural network (ANN), and deep learning (DL) and ensemble methods. We present a detailed review on these three approaches for Alzheimer’s with possible future directions.
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Affiliation(s)
- M. Tanveer
- Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India
| | - B. Richhariya
- Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India
| | - R. U. Khan
- Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore, India
| | - A. H. Rashid
- Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Indore 8 School of Computer Science and Engineering, National Institute of Science and Technology, Berhampur, Odisha, India
| | - P. Khanna
- PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, India
| | - M. Prasad
- Centre for Artificial Intelligence, School of Computer Science, FEIT, University of Technology Sydney, Sydney, Australia
| | - C. T. Lin
- Centre for Artificial Intelligence, School of Computer Science, FEIT, University of Technology Sydney, Sydney, Australia
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Rodrigues PM, Freitas D, Teixeir JP. Alzheimer Electroencephalogram Temporal Events Detection by K-means. ACTA ACUST UNITED AC 2012. [DOI: 10.1016/j.protcy.2012.09.095] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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