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 …

Automated Schizophrenia detection using local descriptors with EEG signals

TS Kumar, KN Rajesh, S Maheswari… - … Applications of Artificial …, 2023 - Elsevier
Schizophrenia (SZ) is a severe mental disorder characterized by behavioral imbalance and
impaired cognitive ability. This paper proposes a local descriptors-based automated …

Fractal dimension analysis of resting state functional networks in schizophrenia from EEG signals

J Ruiz de Miras, AJ Ibáñez-Molina… - Frontiers in Human …, 2023 - frontiersin.org
Fractal dimension (FD) has been revealed as a very useful tool in analyzing the changes in
brain dynamics present in many neurological disorders. The fractal dimension index (FDI) is …

Pycaret for the evaluation of classification methods in order to set up a decision making system for the early diagnosis of schizophrenia by EEG

PFT Nanfack, ET Fute, PA Ele - 2022 16th International …, 2022 - ieeexplore.ieee.org
According to the World Health Organization, approximately 24 million people suffer from
schizophrenia worldwide. However, there is no clinical examination to diagnose this …

[PDF][PDF] APPLICATION OF MACHINE LEARNING TECHNIQUES FOR DISTINGUISHING SCHIZOPHRENIA PATIENTS FROM HEALTHY SUBJECTS USING FRONTAL …

D Dankinas, E Budginaitė, S Mėlynytė, A Šiurkutė… - SVEIKATOS, 2023 - sam.lrv.lt
Machine learning (ML) represents a set of artificial intelligence techniques that can assist in
recognition of schizophrenia by classifying a person as belonging to either clinical or healthy …