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This study investigated functional impairment associated with depression, symptoms that served as the best markers of depression vs. other disorders, as well as depression severity between two depressed sub-groups and other diagnostic comparison groups.
These studies have identified patient populations with conditions such as peripheral cancers or cardiovascular disease, as well as an incidence of depressive symptoms, and they have then assessed the patient's brains for neuronal markers of depression.
Our results supported Hypothesis 1, that markers of depression are observable in Instagram user behavior, and Hypothesis 2, that these depressive signals are detectable in posts made even before the date of first diagnosis.
Our goal was to successfully identify and predict markers of depression in Instagram users' posted photographs.
Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression.
This study aimed to provide evidence on the relationships between markers of depression, anxiety, alexithymia, self-reflection, insight and quality of life in migraine.
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Depression has been associated with decreased blood BDNF concentrations; but it is unclear if low blood BDNF levels are a state or a trait marker of depression.
Instead, functional brain activity to sad facial expressions may be a more accurate diagnostic marker of depression [2].
On the other hand Bourke and colleagues [55] in their review, indicated that it is not clear yet if impairment of emotion recognition is state or trait marker of depression severity.
This would have allowed us to confirm that the findings were related to depression rather than being a peculiarity of the PGC, although this is mitigated by the fact that the PGC is a good proxy marker of depression [3], [4], [5], [6], [7], [8].
Auditory processing has been considered as marker of depression reflecting an underlying serotonergic dysfunction [ 30].
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