Towards a brain‐based predictome of mental illness

B Rashid, V Calhoun - Human brain mapping, 2020 - Wiley Online Library
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …

[HTML][HTML] Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms

M Cao, E Martin, X Li - Translational Psychiatry, 2023 - nature.com
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous
neurodevelopmental disorder in children and has a high chance of persisting in adulthood …

Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models

T Wolfers, CF Beckmann, M Hoogman… - Psychological …, 2020 - cambridge.org
BackgroundThe present paper presents a fundamentally novel approach to model individual
differences of persons with the same biologically heterogeneous mental disorder. Unlike …

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 …

[HTML][HTML] Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

Z Chen, B Hu, X Liu, B Becker, SB Eickhoff, K Miao… - BMC medicine, 2023 - Springer
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …

Classification accuracy of neuroimaging biomarkers in attention-deficit/hyperactivity disorder: effects of sample size and circular analysis

AA Pulini, WT Kerr, SK Loo, A Lenartowicz - … : Cognitive Neuroscience and …, 2019 - Elsevier
Background Motivated by an inconsistency between reports of high diagnosis-classification
accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this …

Refinement by integration: aggregated effects of multimodal imaging markers on adult ADHD

T Wolfers, AL Arenas, AMH Onnink, J Dammers… - Journal of Psychiatry and …, 2017 - jpn.ca
Background: Attention-deficit/hyperactivity disorder (ADHD) is biologically heterogeneous,
with different biological predispositions—mediated through developmental processes …

[HTML][HTML] Decreased olfactory discrimination is associated with impulsivity in healthy volunteers

AM Herman, H Critchley, T Duka - Scientific reports, 2018 - nature.com
In clinical populations, olfactory abilities parallel executive function, implicating shared
neuroanatomical substrates within the ventral prefrontal cortex. In healthy individuals, the …

Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis

L Tian, H Zheng, K Zhang, J Qiu, X Song, S Li… - Journal of Affective …, 2024 - Elsevier
Background The aim of this study was to investigate the diagnostic value of ML techniques
based on sMRI or/and fMRI for ADHD. Methods We conducted a comprehensive search …

[HTML][HTML] Mid-Luteal Olfactory Abilities Reveal Healthy Women's Emotional and Cognitive Functions

F Yao, K Chen, Y Zhuang, X Shen… - Frontiers in Neuroscience, 2022 - frontiersin.org
Ovarian hormones modulate women's physical and psychological states periodically.
Although the olfactory function is increasingly recognized as a reflection of physical and …