ArticleScientific reports2022
A new strategy for the early detection of alzheimer disease stages using multifractal geometry analysis based on K-Nearest Neighbor algorithm.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.
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16 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer's Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges.Sensors (Basel, Switzerland) · 2026Pooled it
- Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.JMIR aging · 2024Pooled it
- Application of machine learning in measurement of ageing and geriatric diseases: a systematic review.BMC geriatrics · 2023Pooled it
- Centralized Review of Alzheimer's Disease and Related Dementias Biomedical Repositories and Computational Methods.Bioengineering (Basel, Switzerland) · 2026Review
- Recent Advances in Nanoparticle-Based Drug Delivery Strategies to Cross the Blood-Brain Barrier in Targeted Treatment of Alzheimer's Disease.Pharmaceutics · 2026Review
- Artificial intelligence techniques for classification of Alzheimer's disease using neuroimaging data: a review.Frontiers in artificial intelligence · 2026Review
- A Scoping Review of Machine Learning-Based Prediction of Alzheimer's Disease Using Blood Biomarkers.Biomedical engineering and computational biology · 2026Review
- Precise diagnosis of Alzheimer's disease based on sex-specific gray matter characteristics.Frontiers in neuroscience · 2026Article
- Article
- Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development.JMIRx med · 2025Article
- Retracted: A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study.JMIR medical informatics · 2025Article
- Article
- Prediction of 30-day in-hospital mortality in older UGIB patients using a simplified risk score and comparison with AIMS65 score.BMC geriatrics · 2024Article
- A multi-omics study to monitor senescence-associated secretory phenotypes of Alzheimer's disease.Annals of clinical and translational neurology · 2024Article
- HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy.International journal of ophthalmology · 2024Article
- Alzheimer's disease: new insight in assessing of amyloid plaques morphologies using multifractal geometry based on Naive Bayes optimized by random forest algorithm.Scientific reports · 2023Article
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Abstract
Alzheimer's Disease (AD) is considered one of the most diseases that much prevalent among elderly people all over the world. AD is an incurable neurodegenerative disease affecting cognitive functions and were characterized by progressive and collective functions deteriorating. Remarkably, early detection of AD is essential for the development of new and invented treatment strategies. As Dementia causes irreversible damage to the brain neurons and leads to changes in its structure that can be described adequately within the framework of multifractals. Hence, the present work focus on developing a promising and efficient computing technique to pre-process and classify the AD disease especially in the early stages using multifractal geometry to extract the most changeable features due to AD. Then, A machine learning classification algorithm (K-Nearest Neighbor) has been implemented in order to classify and detect the main four early stages of AD. Two datasets have been used to ensure the validation of the proposed methodology. The proposed technique has achieved 99.4% accuracy and 100% sensitivity. The comparative results show that the proposed classification technique outperforms is recent techniques in terms of performance measures.
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