[HTML][HTML] The role of machine learning in diagnosing bipolar disorder: sco** review

Z Jan, N Ai-Ansari, O Mousa, A Abd-Alrazaq… - Journal of medical …, 2021 - jmir.org
Background Bipolar disorder (BD) is the 10th most common cause of frailty in young
individuals and has triggered morbidity and mortality worldwide. Patients with BD have a life …

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

AG Bryant, K Aquino, L Parkes, A Fornito… - PLoS computational …, 2024 - journals.plos.org
The brain's complex distributed dynamics are typically quantified using a limited set of
manually selected statistical properties, leaving the possibility that alternative dynamical …

A generalizable method for automated quality control of functional neuroimaging datasets

M Kollada, Q Gao, MS Mellem, T Banerjee… - Explainable AI in …, 2021 - Springer
Over the last twenty five years, advances in the collection and analysis of functional
magnetic resonance imaging (fMRI) data have enabled new insights into the brain basis of …

Systems and methods for processing mri data

M Kollada, HAG CABEZAS, LIU Yuelu… - US Patent App. 17 …, 2022 - Google Patents
The present disclosure provides systems and methods for automating the QC of MRI scans.
Particularly, the inventors trained machine learning classifiers using features derived from …

Genética e neuroimagem no TDAH e fenótipos relacionados

RB Cupertino - 2019 - lume.ufrgs.br
O Transtorno de Déficit de Atenção/Hiperatividade (TDAH) é altamente prevalente e leva a
prejuízos em diversos domínios. Compreender mais sobre sua etiologia pode romper …