ArticleScientific reports2022
Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.
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 13 papers.
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Who cites it
13 citing papers in PubMed, 35 citations in OpenAlex.
- Multimodal Assessment of Consciousness with Brain-Computer Interfaces and Artificial Intelligence: From Acquired Brain Injury to Neurodegenerative Disease.Journal of clinical medicine · 2026Review
- Comparative evaluation of automated MRI-based brain volumetry software for estimating cognitive domains in early Alzheimer's disease.BMC medical imaging · 2026Article
- Comparative analysis of multiple deep learning models with mitigation-driven approaches for enhanced Alzheimer's disease classification.Scientific reports · 2025Article
- A computational ontology framework for the synthesis of multi-level pathology reports from brain MRI scans.Journal of Alzheimer's disease : JAD · 2025Article
- High-resolution conditional MR image synthesis through the PACGAN framework.Scientific reports · 2025Article
- Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.International journal of molecular sciences · 2025Review
- Recent Advances in the Application of Artificial Intelligence in Alzheimer's Disease.Current Alzheimer research · 2025Review
- Multi-model deep learning for dementia detection: addressing data and model limitations.Frontiers in neuroscience · 2025Article
- Article
- Deep learning-based, fully automated, pediatric brain segmentation.Scientific reports · 2024Article
- An explainable machine learning approach for Alzheimer's disease classification.Scientific reports · 2024Article
- Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies.Neurology and therapy · 2023Review
- Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine.Computational and structural biotechnology journal · 2023Review
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Authors and funding
20 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging and may influence prognosis. We investigated whether VUNO Med-DeepBrain AD (DBAD) using a deep learning algorithm can be employed as a decision support service for the diagnosis of AD. This study included 98 elderly participants aged 60 years or older who visited the Seoul Asan Medical Center and the Korea Veterans Health Service. We administered a standard diagnostic assessment for diagnosing AD. DBAD and three panels of medical experts (ME) diagnosed participants with normal cognition (NC) or AD using T1-weighted magnetic resonance imaging. The accuracy (87.1% for DBAD and 84.3% for ME), sensitivity (93.3% for DBAD and 80.0% for ME), and specificity (85.5% for DBAD and 85.5% for ME) of both DBAD and ME for diagnosing AD were comparable; however, DBAD showed a higher trend in every analysis than ME diagnosis. DBAD may support the clinical decisions of physicians who are not specialized in AD; this may enhance the accessibility of AD diagnosis and treatment.
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