Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …
symptoms that appear in early childhood. ASD is also associated with communication …
Domain Adaptation and Generalization of Functional Medical Data: A Systematic Survey of Brain Data
G Sarafraz, A Behnamnia, M Hosseinzadeh… - ACM Computing …, 2024 - dl.acm.org
Despite the excellent capabilities of machine learning algorithms, their performance
deteriorates when the distribution of test data differs from the distribution of training data. In …
deteriorates when the distribution of test data differs from the distribution of training data. In …
Role of artificial intelligence for autism diagnosis using DTI and fMRI: A survey
Autism spectrum disorder (ASD) is a wide range of diseases characterized by difficulties with
social skills, repetitive activities, speech, and nonverbal communication. The Centers for …
social skills, repetitive activities, speech, and nonverbal communication. The Centers for …
Privacy-preserving multi-source domain adaptation for medical data
T Han, X Gong, F Feng, J Zhang… - IEEE journal of …, 2022 - ieeexplore.ieee.org
Great progress has been made in diagnosing medical diseases based on deep learning.
Large-scale medical data are expected to improve deep learning performance further. It is …
Large-scale medical data are expected to improve deep learning performance further. It is …
Domain adaptation and generalization on functional medical images: A systematic survey
G Sarafraz, A Behnamnia, M Hosseinzadeh… - arXiv preprint arXiv …, 2022 - arxiv.org
Machine learning algorithms have revolutionized different fields, including natural language
processing, computer vision, signal processing, and medical data processing. Despite the …
processing, computer vision, signal processing, and medical data processing. Despite the …
Multi-source domain adaptation techniques for mitigating batch effects: A comparative study
The past decade has seen an increasing number of applications of deep learning (DL)
techniques to biomedical fields, especially in neuroimaging-based analysis. Such DL-based …
techniques to biomedical fields, especially in neuroimaging-based analysis. Such DL-based …
Auditory event-related potential differentiates girls with Rett syndrome from their typically-developing peers with high accuracy: Machine learning study
M Sharaev, M Nekrashevich, D Kostanian… - Cognitive Systems …, 2024 - Elsevier
Rett Syndrome (RTT) is a rare neurodevelopmental disorder caused by mutation in the
MECP2 gene. No cures are still available, but several clinical trials are ongoing. Here we …
MECP2 gene. No cures are still available, but several clinical trials are ongoing. Here we …
Assessing the Impact of Preprocessing Pipelines on fMRI Based Autism Spectrum Disorder Classification: ABIDE II Results
FE Bazay, A Drissi El Maliani - International Conference on Engineering …, 2024 - Springer
Resting-state functional MRI (rs-fMRI), a tool for assessing the brain's spontaneous activity,
plays a crucial role in understanding functional connectivity, contingent on the precision of …
plays a crucial role in understanding functional connectivity, contingent on the precision of …
Graph fusion prediction of autism based on attentional mechanisms
Y Cheng, L Liu, X Gu, Z Lu, Y Xia, J Chen… - Journal of Biomedical …, 2023 - Elsevier
Autism spectrum disorder (ASD) is a pervasive developmental disorder, and the earlier
detection and timely intervention for treatment positively affect the prognosis of patients …
detection and timely intervention for treatment positively affect the prognosis of patients …
Domain adaptation in small-scale and heterogeneous biological datasets
Machine learning techniques are steadily becoming more important in modern biology, and
are used to build predictive models, discover patterns, and investigate biological problems …
are used to build predictive models, discover patterns, and investigate biological problems …