Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

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http://www.wikidata.org/entity/Q31046434
Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury.Prediction of lithium response in first-episode mania using the LITHium Intelligent Agent (LITHIA): Pilot data and proof-of-concept.Six Years of Research on the National Institute of Mental Health's Research Domain Criteria (RDoC) Initiative: A Systematic Review.Neuroprogression and illness trajectories in bipolar disorder.Pattern recognition of magnetic resonance imaging-based gray matter volume measurements classifies bipolar disorder and major depressive disorder.Preliminary mapping of the structural effects of age in pediatric bipolar disorder with multimodal MR imaging.e-PTSD: an overview on how new technologies can improve prediction and assessment of Posttraumatic Stress Disorder (PTSD).Brain Subtyping Enhances The Neuroanatomical Discrimination of Schizophrenia.Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?The Staging of Major Mood Disorders: Clinical and Neurobiological Correlates
P2860

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

Item
http://www.wikidata.org/entity/Q31046434
description
2016 nî lūn-bûn
@nan
2016 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Identification and individuali ...... ng scans and machine learning.
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Identification and individuali ...... ng scans and machine learning.
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type
label
Identification and individuali ...... ng scans and machine learning.
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Identification and individuali ...... ng scans and machine learning.
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Identification and individuali ...... ng scans and machine learning.
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Identification and individuali ...... ng scans and machine learning.
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Identification and individuali ...... ng scans and machine learning.
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10.1016/J.NEUROIMAGE.2016.02.016
P407
P433
P478
P50
P577
P5875
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P921
P932