Federated learning for medical image analysis with deep neural networks
S Nazir, M Kaleem - Diagnostics, 2023 - mdpi.com
Medical image analysis using deep neural networks (DNN) has demonstrated state-of-the-
art performance in image classification and segmentation tasks, aiding disease diagnosis …
art performance in image classification and segmentation tasks, aiding disease diagnosis …
Federated learning for medical image analysis: A survey
Abstract Machine learning in medical imaging often faces a fundamental dilemma, namely,
the small sample size problem. Many recent studies suggest using multi-domain data …
the small sample size problem. Many recent studies suggest using multi-domain data …
Source free semi-supervised transfer learning for diagnosis of mental disorders on fmri scans
The high prevalence of mental disorders gradually poses a huge pressure on the public
healthcare services. Deep learning-based computer-aided diagnosis (CAD) has emerged to …
healthcare services. Deep learning-based computer-aided diagnosis (CAD) has emerged to …
An Umbrella Review of the Fusion of fMRI and AI in Autism
D Giansanti - Diagnostics, 2023 - mdpi.com
The role of functional magnetic resonance imaging (fMRI) is assuming an increasingly
central role in autism diagnosis. The integration of Artificial Intelligence (AI) into the realm of …
central role in autism diagnosis. The integration of Artificial Intelligence (AI) into the realm of …
Attention-like multimodality fusion with data augmentation for diagnosis of mental disorders using MRI
The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and
therapy to reduce patients' suffering. Facing such an urgent public health problem …
therapy to reduce patients' suffering. Facing such an urgent public health problem …
[HTML][HTML] A multi-classifier-based recommender system for early autism spectrum disorder detection using machine learning
Efficient and effective medical diagnostic systems are needed for Autism Spectrum Disorder
(ASD) detection and treatment. Healthcare specialists generates extensive remarks on …
(ASD) detection and treatment. Healthcare specialists generates extensive remarks on …
Dynamic multi-site graph convolutional network for autism spectrum disorder identification
Multi-site learning has attracted increasing interests in autism spectrum disorder (ASD)
identification tasks by its efficacy on capturing data heterogeneity of neuroimaging taken …
identification tasks by its efficacy on capturing data heterogeneity of neuroimaging taken …
FAM: Adaptive federated meta-learning for MRI data
Federated learning enables multiple clients to collaborate to train a model without sharing
data. Clients with insufficient data or data diversity participate in federated learning to learn a …
data. Clients with insufficient data or data diversity participate in federated learning to learn a …
Preserving specificity in federated graph learning for fMRI-based neurological disorder identification
Resting-state functional magnetic resonance imaging (rs-fMRI) offers a non-invasive
approach to examining abnormal brain connectivity associated with brain disorders. Graph …
approach to examining abnormal brain connectivity associated with brain disorders. Graph …
Enhancing psychiatric rehabilitation outcomes through a multimodal multitask learning model based on BERT and TabNet: An approach for personalized treatment …
H Yang, D Zhu, S He, Z Xu, Z Liu, W Zhang, J Cai - Psychiatry Research, 2024 - Elsevier
Evaluating the rehabilitation status of individuals with serious mental illnesses (SMI)
necessitates a comprehensive analysis of multimodal data, including unstructured text …
necessitates a comprehensive analysis of multimodal data, including unstructured text …