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Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques

Alejandro Puente-Castro, Enrique Fernandez-Blanco, Alejandro Pazos, Cristian R. Munteanu
<span title="2020-04-18">2020</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdwg5aetkjbgpga7kn2jevifmi" style="color: black;">Computers in Biology and Medicine</a> </i> &nbsp;

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They demand fast and precise assessment in the diagnosis of AD in the earliest and hardest to detect stages.  ...  Early detection is crucial to prevent the progression of Alzheimer's disease (AD). Thus, specialists can begin preventive treatment as soon as possible.  ...  Acknowledgments The authors would like to thank the support from the CESGA, where many of the tests were run.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2020.103764">doi:10.1016/j.compbiomed.2020.103764</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32421658">pmid:32421658</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iz5cpzfqdvggviu5srdzz4lvtu">fatcat:iz5cpzfqdvggviu5srdzz4lvtu</a> </span>
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Alejandro Puente-Castro, Enrique Fernandez-Blanco, Alejandro Pazos, Cristian R. Munteanu. "Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques." Computers in Biology and Medicine (2020) 103764

System for Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques

Alejandro Puente-Castro, Cristian Robert Munteanu, Enrique Fernandez-Blanco
<span title="2019-08-01">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tmebwgnfrvem5c5r53x7zxx3yq" style="color: black;">Proceedings (MDPI)</a> </i> &nbsp;

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Automatic detection of Alzheimer's disease is a very active area of research.  ...  This paper proposes a system for the detection of the disease by means of Deep Learning techniques in magnetic resonance imaging (MRI).  ...  The objective of this work is the use of Deep Learning techniques to support an early diagnosis of Alzheimer's disease through the analysis of conventional sagittal MRI images from two reference sets of  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/proceedings2019021028">doi:10.3390/proceedings2019021028</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wydxkytizzgarfbsk52mmko3g4">fatcat:wydxkytizzgarfbsk52mmko3g4</a> </span>
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Alejandro Puente-Castro, Cristian Robert Munteanu, Enrique Fernandez-Blanco. "System for Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques." Proceedings (MDPI) 21.1 (2019) 28

Alzheimer's Disease Diagnosis using Deep Learning Techniques

<span title="2020-02-29">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;

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A thorough review of various algorithms of deep learning for diagnosis of Alzheimer's disease is done, in which this disease is a progressive brain disorder that destroy the brain memory gradually, it  ...  Deep learning is one of the machine learning approach which has shown promising results and performance as compare to traditional algorithms of machine learning in terms of high dimensional data of MRI  ...  Alzheimer's Disease Diagnosis using Deep Learning Techniques Ahmad Waleed Salehi, Preety Baglat, Gaurav Gupta These computers aided detection and diagnosis perform by deep learning algorithms can help  ... 
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"Alzheimer's Disease Diagnosis using Deep Learning Techniques." International Journal of Engineering and Advanced Technology 9.3 (2020) 874-880

Machine Learning Based Approach for Detection of Alzheimer's Disease

Maskeen kaur, Amanjot kaur
<span title="2021-11-12">2021</span> <i title="International Journal of Scientific and Research Publications (IJSRP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6ht2eimu5nflxkqur2pzauntxu" style="color: black;">International Journal of Scientific and Research Publications (IJSRP)</a> </i> &nbsp;

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paper, prediction of AD based on a deep neural network from magnetic resonance imaging (MRI) is proposed.Recognizing signs early as much as possible is important as disorder enhancing drugs might be best  ...  3D MRI data plays a very important role as it can come up with the better results for the proper diagnosis of the particular disease.  ...  Al-falluji and Abdulmunem (Al-falluji, 2017)conducted the survey on magnetic resonance-based techniques for detecting Alzheimer's disease.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.29322/ijsrp.11.11.2021.p11942">doi:10.29322/ijsrp.11.11.2021.p11942</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cssn5miyurhvznn5wq7gague2i">fatcat:cssn5miyurhvznn5wq7gague2i</a> </span>
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Maskeen kaur, Amanjot kaur. "Machine Learning Based Approach for Detection of Alzheimer's Disease." International Journal of Scientific and Research Publications (IJSRP) 11.11 (2021) 341-343

Applying deep learning models on structural MRI for stage prediction of Alzheimer's disease

<span title="">2019</span> <i title="The Scientific and Technological Research Council of Turkey"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ewkcv4t6w5f2pc7j2w426gox7a" style="color: black;">Turkish Journal of Electrical Engineering and Computer Sciences</a> </i> &nbsp;

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The proposed deep learning-based model might serve as an efficient and practical diagnostic tool when MRI data are integrated with other clinical tests.  ...  The CNN models achieved accuracy values around 0.8 for diagnosis of both Alzheimer's disease and mild cognitive impairment.  ...  Compared to many studies on the diagnosis of Alzheimer's disease, fewer studies have attempted an automatic diagnosis of MCI patients.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3906/elk-1904-172">doi:10.3906/elk-1904-172</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/atalfzuszbbvnak3rdjzrnfcnu">fatcat:atalfzuszbbvnak3rdjzrnfcnu</a> </span>
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200211203058/http://journals.tubitak.gov.tr/elektrik/issues/elk-20-28-1/elk-28-1-14-1904-172.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9e/2e/9e2e2bad9fb3121e3a8ff3bb071909455718baab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3906/elk-1904-172"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>
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"Applying deep learning models on structural MRI for stage prediction of Alzheimer's disease." Turkish Journal of Electrical Engineering and Computer Sciences 28.1 (2019)

Machine Learning for Detection of Cognitive Impairment

Valeria Diaz, Guillermo Rodríguez
<span title="">2022</span> <i title="Obuda University"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uwcqb6ghifgnlk73meee4juzsy" style="color: black;">Acta Polytechnica Hungarica</a> </i> &nbsp;

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decline escalates into the early stage of dementia, e.g., Alzheimer's disease (AD).  ...  The result of this research shows ML algorithms can identify AD, in early stages, with an 80% accuracy, using a Deep Learning (DL) algorithm.  ...  Results and Discussions In this research, we present an approach based on supervised automatic learning for the early detection of Alzheimer's disease.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.12700/aph.19.5.2022.5.10">doi:10.12700/aph.19.5.2022.5.10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pzyv7o4wnfd4ljbyvkb4xo4l4e">fatcat:pzyv7o4wnfd4ljbyvkb4xo4l4e</a> </span>
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Valeria Diaz, Guillermo Rodríguez. "Machine Learning for Detection of Cognitive Impairment." Acta Polytechnica Hungarica 19.5 (2022) 195-213

Alzheimer's Disease Classification Using Deep CNN

Shikha Agrawal, Neha Sunil Pandharkar, Pooja Arvind Khandelwal, Pratiksha Ashok Pandhare, Janhavi Sanjay Deoghare
<span title="2021-05-20">2021</span> <i title="Technoscience Academy"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cwo66igunvdiplkdqwpqsgzpem" style="color: black;">International Journal of Scientific Research in Computer Science Engineering and Information Technology</a> </i> &nbsp;

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Especially in the world, the deep learning algorithm has become a technique of choice for analyzing medical images rapidly.  ...  Alzheimer's disease (AD) is regarded to be the most prevalent cause of dementia, and only 1 in 4 individuals with Alzheimer's are estimated to be diagnosed correctly on time.  ...  The overall strategy is based on elimination diagnosis, i.e. until Alzheimer's disease is the last choice, all else does the decision.  ... 
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Shikha Agrawal, Neha Sunil Pandharkar, Pooja Arvind Khandelwal, Pratiksha Ashok Pandhare, Janhavi Sanjay Deoghare. "Alzheimer's Disease Classification Using Deep CNN." International Journal of Scientific Research in Computer Science Engineering and Information Technology (2021) 325-331

ANALYSIS OF ALZHEIMER DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES

B. Hemalatha, Dr. M. Renukadevi
<span title="2021-03-05">2021</span> <i title="Auricle Technologies, Pvt., Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ti2mgqbqpfhhzla5hdk62fee2y" style="color: black;">Information Technology in Industry</a> </i> &nbsp;

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Modern research has shown that deep learning is a proficient technique for solving numerous problems of image recognition, but most of these published approaches owe their performance to training on a  ...  Alzheimer's Disease (AD) is referred to as one of the highest non-unusual neurodegenerative disorders that inflict eternal harm to the memory-associated brain cells and wonder skills.  ...  The selected features are then redirected to machine learning algorithms that classify PET images into one of the possible categories based on pattern recognition techniques.  ... 
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B. Hemalatha, Dr. M. Renukadevi. "ANALYSIS OF ALZHEIMER DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES." Information Technology in Industry (2021) 519-525

Healthcare Techniques Through Deep Learning: Issues, Challenges and Opportunities

Dur-E-Maknoon Nisar, Rashid Amin, Noor-Ul-Huda Shah, Mohammed A. Al Ghamdi, Sultan H. Almotiri, Meshrif Alruily
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;

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The diagnosis, which is based on the scanned image, can be very subjective. The Computer-Aided Diagnosis (CAD) comes up with an actual assessment of the current primary disease process.  ...  Deep learning can take millions of images based on their similarities, making clusters of these images.  ... 
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Dur-E-Maknoon Nisar, Rashid Amin, Noor-Ul-Huda Shah, Mohammed A. Al Ghamdi, Sultan H. Almotiri, Meshrif Alruily. "Healthcare Techniques Through Deep Learning: Issues, Challenges and Opportunities." IEEE Access (2021) 1-1

A Review on the use of Artificial Intelligence Techniques in Brain MRI Analysis

Shruti Agarwal, Department of Computer Science Engineering, BBD University, Lucknow, India
<span title="2021-06-06">2021</span> <i title="A2Z Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cu7f43uyzzcblexero4qhhh2te" style="color: black;">Journal of Informatics Electrical and Electronics Engineering (JIEEE)</a> </i> &nbsp;

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Efforts are useful in figuring out popular studies works in AI primarily based on mind MRI analysis throughout specific issues.  ...  Analysis of numerous articles to create a taxonomy of research subject matters and results was done. The article is classed which might be posted between 2000 and 2018 with this taxonomy.  ...  In 2019, Siyuan Lu et. al., [33] worked to automatically detect pathological brain in magnetic resonance images (MRI) based on deep learning structure and transfer learning.  ... 
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Shruti Agarwal, Department of Computer Science Engineering, BBD University, Lucknow, India. "A Review on the use of Artificial Intelligence Techniques in Brain MRI Analysis." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2.2 (2021) 1-15

Development of a Deep Learning Model for Early Alzheime's Disease Detection from Structural MRIs and External Validation on an Independent Cohort [article]

Sheng Liu, Arjun Masurkar, Henry Rusinek, Jingyun Chen, Ben Zhang, Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian
<span title="2021-06-01">2021</span> <i title="Cold Spring Harbor Laboratory"> medRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>

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These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection  ...  Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials.  ...  Figure 1 : 1 Overview of the deep learning framework and performance for Alzheimer's automatic diagnosis. (a) Deep learning framework used for automatic diagnosis.  ... 
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Sheng Liu, Arjun Masurkar, Henry Rusinek, Jingyun Chen, Ben Zhang, Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian. "Development of a Deep Learning Model for Early Alzheime's Disease Detection from Structural MRIs and External Validation on an Independent Cohort." medRxiv (2021)

Alzheimer's Disease: A Survey

Harshitha, Gowthami Chamarajan, Charishma Y
<span title="2021-06-22">2021</span> <i title="Lamintang Education and Training Centre"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rb3powughjegrfy6lkuj3mmw2q" style="color: black;">International Journal of Artificial Intelligence</a> </i> &nbsp;

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In recent years, Neuroimaging combined with machine learning techniques have been used for detection of Alzheimer's disease.  ...  Alzheimer's Diseases (AD) is one of the type of dementia. This is one of the harmful disease which can lead to death and yet there is no treatment.  ...  Suh, et al [18] they have used deep learning based automatic brain segmentation and classification algorithm for accurate diagnosis of AD.  ... 
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Harshitha, Gowthami Chamarajan, Charishma Y. "Alzheimer's Disease: A Survey." International Journal of Artificial Intelligence 8.1 (2021) 33-39

2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q2z26obphvchndqieqd65vltle" style="color: black;">IEEE journal of biomedical and health informatics</a> </i> &nbsp;

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., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre, C., JBHI Jan  ...  on Matrix Completion Algorithm; JBHI Dec. 2020 3630-3641 Jiang, S., see Zhou, Z., JBHI Jan. 2020 194-204 Jiang, X., see Zhou, Z., JBHI April 2020 943-956 Jiang, Y., see Yu, R., JBHI Feb. 2020 486-  ...  Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.  ... 
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"2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24." IEEE journal of biomedical and health informatics 24.12 (2020) 3642-3717

DIAGNOSIS OF ALZHEIMER'S DISEASE BY THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK USING UNSUPERVISED FEATURE LEARNING METHOD

Sarah A. Soliman, El-Sayed A. El-Dahshan, Abdel-Badeeh M. Salem
<span title="2021-11-12">2021</span> <i title="Egypts Presidential Specialized Council for Education and Scientific Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wloedbdfcffl3cdn2dehdftvby" style="color: black;">International Journal of Intelligent Computing and Information Sciences</a> </i> &nbsp;

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The rise of Deep Learning in the past two decades has prompted research into solutions to help improve Alzheimer's diagnosis based on neuroimaging data.  ...  The second stage involves using a to differentiate between the health status and diseased status based on the learned records and MRI scan of the brain.  ...  The authors of ref [22] used a new framework based on deep learning methodologies for early diagnosis of Alzheimer's disease, which included stacked sparse auto-encoders and a softmax output layer.  ... 
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Sarah A. Soliman, El-Sayed A. El-Dahshan, Abdel-Badeeh M. Salem. "DIAGNOSIS OF ALZHEIMER'S DISEASE BY THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK USING UNSUPERVISED FEATURE LEARNING METHOD." International Journal of Intelligent Computing and Information Sciences 0.0 (2021) 1-15

EARLY DETECTION OF ALZHEIMERS DISEASE USING MACHINE LEARNING TECHNIQUES

Ariful Islam Khan, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Saiful Islam, Sanjida Tasnim Shorno, Sumonto Sarker, Abubakar Siddik, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh
<span title="2019-11-30">2019</span> <i title="International Journal Of Advanced Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mmn4oevdbfbf5leqgrynhcypzm" style="color: black;">International Journal of Advanced Research</a> </i> &nbsp;

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Thus the proposed model performs a better job on regarding the early diagnosis of Alzheimer's Disease. -Performance Comparison Sl.  ...  The device will automatically collect necessary information from the subjects through wearable sensors. Then it will use the data against the machine learning model for disease diagnosis. 2.  ... 
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<span class="ui label basic orange small" title="Szcezepanski OA Journal List">Szczepanski</span>
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Ariful Islam Khan, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Saiful Islam, Sanjida Tasnim Shorno, Sumonto Sarker, Abubakar Siddik, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh, Department of Electronics and Communication Engineering, Faculty of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Dinajpur, Bangladesh. "EARLY DETECTION OF ALZHEIMERS DISEASE USING MACHINE LEARNING TECHNIQUES." International Journal of Advanced Research 7.11 (2019) 235-242

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