Journal: Sensors (Basel, Switzerland)

Article Title: Evaluation of Vertical Ground Reaction Forces Pattern Visualization in Neurodegenerative Diseases Identification Using Deep Learning and Recurrence Plot Image Feature Extraction

doi: 10.3390/s20143857

Figure Lengend Snippet: Architecture of the proposed method convolutional neural network (CNN).

Article Snippet: A pretrained AlexNet CNN was utilized from MATLAB R2018a Deep Learning Toolbox TM in the system [ ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Evaluation of Vertical Ground Reaction Forces Pattern Visualization in Neurodegenerative Diseases Identification Using Deep Learning and Recurrence Plot Image Feature Extraction

doi: 10.3390/s20143857

Figure Lengend Snippet: Average execution time of the proposed method.

Article Snippet: A pretrained AlexNet CNN was utilized from MATLAB R2018a Deep Learning Toolbox TM in the system [ ].

Techniques: Transformation Assay

Journal: Diagnostics

Article Title: A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging

doi: 10.3390/diagnostics15060789

Figure Lengend Snippet: Summary of Related Works.

Article Snippet: Saim et al. (2024) [ ] , Nine CNN architectures (AlexNet, Inception, EfficientNet-b0, etc.) , Kaggle Alzheimer’s dataset ADNI dataset , 5091 Images (Train) 1273 Images (Test) , Feature extraction using pretrained CNNs (fully connected, inception-based, residual-based, etc.); classification using MSVM, KNN, DT; , Kaggle: ADNI: 78.54% (MSVM) , Early detection and staging of AD using neuroimaging biomarkers , Performance on ADNI dataset lower; needs further validation on larger and more diverse datasets..

Techniques: Biomarker Discovery, Imaging

Journal: Diagnostics

Article Title: A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging

doi: 10.3390/diagnostics15060789

Figure Lengend Snippet: Comprehensive Comparison with Other Existing Studies.

Article Snippet: Saim et al. (2024) [ ] , Nine CNN architectures (AlexNet, Inception, EfficientNet-b0, etc.) , Kaggle Alzheimer’s dataset ADNI dataset , 5091 Images (Train) 1273 Images (Test) , Feature extraction using pretrained CNNs (fully connected, inception-based, residual-based, etc.); classification using MSVM, KNN, DT; , Kaggle: ADNI: 78.54% (MSVM) , Early detection and staging of AD using neuroimaging biomarkers , Performance on ADNI dataset lower; needs further validation on larger and more diverse datasets..

Techniques: Comparison, Stripping Membranes, Extraction, Biomarker Discovery, Imaging