Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review

Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …

Machine learning techniques for the Schizophrenia diagnosis: a comprehensive review and future research directions

S Verma, T Goel, M Tanveer, W Ding, R Sharma… - Journal of Ambient …, 2023 - Springer
Schizophrenia (SCZ) is a brain disorder where different people experience different
symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long …

Optimizing feature subset for schizophrenia detection using multichannel EEG signals and rough set theory

S Srinivasan, SD Johnson - Cognitive Neurodynamics, 2024 - Springer
Schizophrenia (SZ) is a mental disorder that causes lifelong disorders based on delusions,
cognitive deficits, and hallucinations. By visual assessment, SZ diagnosis is time-consuming …

Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis

R Zhang, J Ren, X Lei, Y Wang, X Chen, L Fu… - Progress in Neuro …, 2024 - Elsevier
Background Schizophrenia is a prevalent mental disorder, leading to severe disability.
Currently, the absence of objective biomarkers hinders effective diagnosis. This study was …

[HTML][HTML] Multi-modal MRI for objective diagnosis and outcome prediction in depression

J Pilmeyer, R Lamerichs, S Schielen… - NeuroImage: Clinical, 2024 - Elsevier
Abstract Research Purpose The low treatment effectiveness in major depressive disorder
(MDD) may be caused by the subjectiveness in clinical examination and the lack of …

Resting-state functional MRI in treatment-resistant schizophrenia

N Tuovinen, A Hofer - Frontiers in Neuroimaging, 2023 - frontiersin.org
Background Abnormalities in brain regions involved in the pathophysiology of schizophrenia
(SCZ) may present insight into individual clinical symptoms. Specifically, functional …

MCE: Medical Cognition Embedded in 3D MRI feature extraction for advancing glioma staging

H Xue, H Lu, Y Wang, N Li, G Wang - Plos one, 2024 - journals.plos.org
In recent years, various data-driven algorithms have been applied to the classification and
staging of brain glioma MRI detection. However, the restricted availability of brain glioma …

LitefusionNet: Boosting the Performance for Medical Image Classification with an Intelligent and Lightweight Feature Fusion Network

S Asif, Q Ain, R Al-Sabri, M Abdullah - Journal of Computational Science, 2024 - Elsevier
Medical image analysis plays a crucial role in modern healthcare for accurate diagnosis and
treatment. However, the inherent challenges and limitations posed by the complexity and …

Weighted ordinal connection based functional network classification for schizophrenia disease detection using EEG signal

MR Kose, MK Ahirwal, M Atulkar - Physical and Engineering Sciences in …, 2023 - Springer
A brain connectivity network (BCN) is an advanced approach to examining brain
functionality in various conditions. However, the predictability of the BCN is affected by the …

Ultrasound-based artificial intelligence model for prediction of Ki-67 proliferation index in soft tissue tumors

X Dai, H Lu, X Wang, Y Liu, J Zang, Z Liu… - Academic …, 2024 - academicradiology.org
Rationale and Objectives To investigate the value of deep learning (DL) combined with
radiomics and clinical and imaging features in predicting the Ki-67 proliferation index of soft …