Multimodal machine learning in precision health: A scoping review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
[PDF][PDF] Composite pain biomarker signatures for objective assessment and effective treatment
Pain is a subjective sensory experience that can, mostly, be reported but cannot be directly
measured or quantified. Nevertheless, a suite of biomarkers related to mechanisms, neural …
measured or quantified. Nevertheless, a suite of biomarkers related to mechanisms, neural …
Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models
Importance Schizophrenia and bipolar disorder are severe and complex brain disorders
characterized by substantial clinical and biological heterogeneity. However, case-control …
characterized by substantial clinical and biological heterogeneity. However, case-control …
Brain heterogeneity in schizophrenia and its association with polygenic risk
Importance Between-individual variability in brain structure is determined by gene-
environment interactions, possibly reflecting differential sensitivity to environmental and …
environment interactions, possibly reflecting differential sensitivity to environmental and …
A deep learning based model using RNN-LSTM for the Detection of Schizophrenia from EEG data
R Supakar, P Satvaya, P Chakrabarti - Computers in Biology and Medicine, 2022 - Elsevier
Normal life can be ensured for schizophrenic patients if diagnosed early.
Electroencephalogram (EEG) carries information about the brain network connectivity which …
Electroencephalogram (EEG) carries information about the brain network connectivity which …
Using structural MRI to identify bipolar disorders–13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective
biological markers, such as those based on brain imaging, could aid in clinical management …
biological markers, such as those based on brain imaging, could aid in clinical management …
Areas of uncertainties and unmet needs in bipolar disorders: clinical and research perspectives
This Review discusses crucial areas related to the identification, clinical presentation,
course, and therapeutic management of bipolar disorder, a major psychiatric illness. Bipolar …
course, and therapeutic management of bipolar disorder, a major psychiatric illness. Bipolar …
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 …
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
The effect of polygenic risk scores for major depressive disorder, bipolar disorder and schizophrenia on morphological brain measures: a systematic review of the …
Background Major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia
(SCZ) share clinical features and genetic bases. Magnetic Resonance Imaging (MRI) …
(SCZ) share clinical features and genetic bases. Magnetic Resonance Imaging (MRI) …
Replicating extensive brain structural heterogeneity in individuals with schizophrenia and bipolar disorder
Identifying brain processes involved in the risk and development of mental disorders is a
major aim. We recently reported substantial interindividual heterogeneity in brain structural …
major aim. We recently reported substantial interindividual heterogeneity in brain structural …