ArticleDiagnostics (Basel, Switzerland)2021
Application of Artificial Intelligence in the MRI Classification Task of Human Brain Neurological and Psychiatric Diseases: A Scoping Review.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence support for diagnosis of neurodevelopmental disorders during childhood: an umbrella review.Frontiers in psychiatry · 2026Pooled 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
- Artificial Intelligence for Mental Health Monitoring: A Solution for Digital Behavioral Health Care and Education-An Umbrella Review.Health science reports · 2026Review
- Machine learning helps predict early onset psychosis with serum protein biomarkers, neuropsychometry, and clinicodemographic data.Scientific reports · 2025Article
- Machine learning algorithms and artificial neural networks for predicting schizophrenia using orbital parameters.Scientific reports · 2025Article
- Integrated Ultra-Wideband Microwave System to Measure Composition Ratio Between Fat and Muscle in Multi-Species Tissue Types.Sensors (Basel, Switzerland) · 2025Article
- Deep learning approaches for classification tasks in medical X-ray, MRI, and ultrasound images: a scoping review.BMC medical imaging · 2025Article
- Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review.Journal of pharmacy & bioallied sciences · 2025Review
- Lights and Shadows on Artificial Intelligence in Glaucoma: Transforming Screening, Monitoring, and Prognosis.Journal of clinical medicine · 2025Review
- The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease.Biomedicines · 2025Review
- The impact of artificial intelligence on drug discovery for neuropsychiatric disorders.EXCLI journal · 2025Review
- Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review.Experimental biology and medicine (Maywood, N.J.) · 2025Article
- Transcriptional Patterns of Nodal Entropy Abnormalities in Major Depressive Disorder Patients with and without Suicidal Ideation.Research (Washington, D.C.) · 2025Article
- Bio-inspired feature selection for early diagnosis of Parkinson's disease through optimization of deep 3D nested learning.Scientific reports · 2024Article
- Aggregated Pattern Classification Method for improving neural disorder stage detection.Brain and behavior · 2024Article
- Sex classification from functional brain connectivity: Generalization to multiple datasets.Human brain mapping · 2024Article
- Sex classification from functional brain connectivity: Generalization to multiple datasets Generalizability of sex classifiers.bioRxiv : the preprint server for biology · 2024Article
- Innovative Neuroimaging Biomarker Distinction of Major Depressive Disorder and Bipolar Disorder through Structural Connectome Analysis and Machine Learning Models.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders.Frontiers in neuroscience · 2024Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Artificial intelligence (AI) for medical imaging is a technology with great potential. An in-depth understanding of the principles and applications of magnetic resonance imaging (MRI), machine learning (ML), and deep learning (DL) is fundamental for developing AI-based algorithms that can meet the requirements of clinical diagnosis and have excellent quality and efficiency. Moreover, a more comprehensive understanding of applications and opportunities would help to implement AI-based methods in an ethical and sustainable manner. This review first summarizes recent research advances in ML and DL techniques for classifying human brain magnetic resonance images. Then, the application of ML and DL methods to six typical neurological and psychiatric diseases is summarized, including Alzheimer's disease (AD), Parkinson's disease (PD), major depressive disorder (MDD), schizophrenia (SCZ), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). Finally, the limitations of the existing research are discussed, and possible future research directions are proposed.
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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.