ReviewJournal of personalized medicine2022
Deep Learning-Based Diagnosis of Alzheimer's Disease.
Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.JMIR aging · 2024Pooled it
- Neural Computation-Based Methods for the Early Diagnosis and Prognosis of Alzheimer's Disease Not Using Neuroimaging Biomarkers: A Systematic Review.Journal of Alzheimer's disease : JAD · 2024Pooled it
- SPECT and PET imaging of Alzheimer's disease revisited: from biomarkers to artificial intelligence-based prediction.Annals of nuclear medicine · 2026Review
- Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.Scientific reports · 2026Article
- Applying Multiple Machine Learning Models to Classify Mild Cognitive Impairment from Speech in Community-Dwelling Older Adults.Journal of Intelligence · 2026Article
- PredatorNet: a clinically trustworthy deep learning framework for multi-class Alzheimer's disease classification using MRI.Frontiers in aging neuroscience · 2026Article
- Recent Advancements of Transcranial Direct Current Stimulation and Machine Learning: Methods, Challenges, and Opportunities.Transactions on artificial intelligence · 2026Article
- Cascaded Spatial and Depth Attention UNet for Hippocampus Segmentation.Journal of imaging · 2025Article
- The Role of Quantitative EEG in the Diagnosis of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Machine Learning in Primary Health Care: The Research Landscape.Healthcare (Basel, Switzerland) · 2025Review
- Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.Scientific reports · 2025Article
- Modeling Alzheimer's Disease: A Review of Gene-Modified and Induced Animal Models, Complex Cell Culture Models, and Computational Modeling.Brain sciences · 2025Review
- Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers.International journal of molecular sciences · 2025Article
- A review of artificial intelligence-based brain age estimation and its applications for related diseases.Briefings in functional genomics · 2025Review
- Health effects of intermittent fasting and the role of artificial intelligence technologies in optimizing its clinical translation.AIMS public health · 2025Review
- AD-Diff: enhancing Alzheimer's disease prediction accuracy through multimodal fusion.Frontiers in computational neuroscience · 2025Article
- A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.Actas espanolas de psiquiatria · 2025Article
- Advancements in deep learning for early diagnosis of Alzheimer's disease using multimodal neuroimaging: challenges and future directions.Frontiers in neuroinformatics · 2025Review
- Recent Advances in the Application of Artificial Intelligence in Alzheimer's Disease.Current Alzheimer research · 2025Review
- Machine Learning-Driven GLCM Analysis of Structural MRI for Alzheimer's Disease Diagnosis.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Alzheimer's disease (AD), the most familiar type of dementia, is a severe concern in modern healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth leading cause of mortality in the US. AD is an irreversible, degenerative brain disorder characterized by a loss of cognitive function and has no proven cure. Deep learning techniques have gained popularity in recent years, particularly in the domains of natural language processing and computer vision. Since 2014, these techniques have begun to achieve substantial consideration in AD diagnosis research, and the number of papers published in this arena is rising drastically. Deep learning techniques have been reported to be more accurate for AD diagnosis in comparison to conventional machine learning models. Motivated to explore the potential of deep learning in AD diagnosis, this study reviews the current state-of-the-art in AD diagnosis using deep learning. We summarize the most recent trends and findings using a thorough literature review. The study also explores the different biomarkers and datasets for AD diagnosis. Even though deep learning has shown promise in AD diagnosis, there are still several challenges that need to be addressed.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.