The diagnosis of ASD with MRI: a systematic review and meta-analysis

SJC Schielen, J Pilmeyer, AP Aldenkamp… - Translational …, 2024 - nature.com
While diagnosing autism spectrum disorder (ASD) based on an objective test is desired, the
current diagnostic practice involves observation-based criteria. This study is a systematic …

Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023

M Jafari, D Sadeghi, A Shoeibi, H Alinejad-Rokny… - Applied …, 2024 - Springer
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …

Spatial–temporal co-attention learning for diagnosis of mental disorders from resting-state fMRI data

R Liu, ZA Huang, Y Hu, Z Zhu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Neuroimaging techniques have been widely adopted to detect the neurological brain
structures and functions of the nervous system. As an effective noninvasive neuroimaging …

Map** multi-modal brain connectome for brain disorder diagnosis via cross-modal mutual learning

Y Yang, C Ye, X Guo, T Wu, Y **ang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, the study of multi-modal brain connectome has recorded a tremendous increase
and facilitated the diagnosis of brain disorders. In this paradigm, functional and structural …

A systematic review of intermediate fusion in multimodal deep learning for biomedical applications

V Guarrasi, F Aksu, CM Caruso, F Di Feola… - arxiv preprint arxiv …, 2024 - arxiv.org
Deep learning has revolutionized biomedical research by providing sophisticated methods
to handle complex, high-dimensional data. Multimodal deep learning (MDL) further …

Beyond Discrimination: Generative AI Applications and Ethical Challenges in Forensic Psychiatry

L Tortora - Frontiers in Psychiatry, 2024 - frontiersin.org
The advent and growing popularity of generative artificial intelligence (GenAI) holds the
potential to revolutionise AI applications in forensic psychiatry and criminal justice, which …

[HTML][HTML] A systematic review of deep learning data augmentation in medical imaging: Recent advances and future research directions

T Islam, MS Hafiz, JR Jim, MM Kabir, MF Mridha - Healthcare Analytics, 2024 - Elsevier
Data augmentation involves artificially expanding a dataset by applying various
transformations to the existing data. Recent developments in deep learning have advanced …

Multitask Learning for Joint Diagnosis of Multiple Mental Disorders in Resting-State fMRI

ZA Huang, R Liu, Z Zhu, KC Tan - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Facing the increasing worldwide prevalence of mental disorders, the symptom-based
diagnostic criteria struggle to address the urgent public health concern due to the global …

An explainable deep learning-based method for schizophrenia diagnosis using generative data-augmentation

M Saadatinia, A Salimi-Badr - IEEE Access, 2024 - ieeexplore.ieee.org
Schizophrenia is an example of a rare mental disorder that is challenging to diagnose using
conventional methods. Deep learning methods have been extensively employed to aid in …

Dynamic Graph Representation Learning for Spatio-Temporal Neuroimaging Analysis

R Liu, Y Hu, J Wu, KC Wong, ZA Huang… - IEEE Transactions …, 2025 - ieeexplore.ieee.org
Neuroimaging analysis aims to reveal the information-processing mechanisms of the human
brain in a noninvasive manner. In the past, graph neural networks (GNNs) have shown …