Deep learning in mental health outcome research: a scoping review
Mental illnesses, such as depression, are highly prevalent and have been shown to impact
an individual's physical health. Recently, artificial intelligence (AI) methods have been …
an individual's physical health. Recently, artificial intelligence (AI) methods have been …
Portable technologies for digital phenotyping of bipolar disorder: A systematic review
LF Saccaro, G Amatori, A Cappelli, R Mazziotti… - Journal of affective …, 2021 - Elsevier
Background Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD)
assessment. The development of digital phenotyping promises to improve BD management …
assessment. The development of digital phenotyping promises to improve BD management …
Digital phenotyping using multimodal data
Abstract Purpose of Review Digital phenotyping involves the quantification of in situ
phenotypes using personal digital devices and holds the potential to dramatically reshape …
phenotypes using personal digital devices and holds the potential to dramatically reshape …
[PDF][PDF] Deep learning solution for pathological voice detection using LSTM-based autoencoder hybrid with multi-task learning
KG Dávid Sztahó, TM Gábriel - I14th International Joint …, 2021 - researchgate.net
In this paper, a deep learning approach is introduced to detect pathological voice disorders
from continuous speech. Speech as bio-signal is getting more and more attention as a …
from continuous speech. Speech as bio-signal is getting more and more attention as a …
Cell-Coupled Long Short-Term Memory With -Skip Fusion Mechanism for Mood Disorder Detection Through Elicited Audiovisual Features
In early stages, patients with bipolar disorder are often diagnosed as having unipolar
depression in mood disorder diagnosis. Because the long-term monitoring is limited by the …
depression in mood disorder diagnosis. Because the long-term monitoring is limited by the …
Automatic detection of depression from text data: A systematic literacture review
F Magami, LA Digiampietri - … of the XVI Brazilian Symposium on …, 2020 - dl.acm.org
Depression is a mental disorder that affects hundreds of millions of people worldwide, with
potentially serious consequences if left without treatment. Despite that, many people still …
potentially serious consequences if left without treatment. Despite that, many people still …
Exploring macroscopic and microscopic fluctuations of elicited facial expressions for mood disorder classification
In the clinical diagnosis of mood disorder, a large proportion of patients with bipolar disorder
(BD) are misdiagnosed as having unipolar depression (UD). Generally, long-term tracking is …
(BD) are misdiagnosed as having unipolar depression (UD). Generally, long-term tracking is …
[PDF][PDF] Detection of Bipolar Disorder Using Machine Learning with MRI.
R Sujatha, K Tejesh, H Krithi, HR Shri - ISIC, 2021 - ceur-ws.org
Bipolar disorder is a mental ailment caused by maximal mood swings with emotional highs
and lows. Nowadays, this has become the most common abnormality related to mental …
and lows. Nowadays, this has become the most common abnormality related to mental …
Exploring microscopic fluctuation of facial expression for mood disorder classification
In clinical diagnosis of mood disorder, depression is one of the most common psychiatric
disorders. There are two major types of mood disorders: major depressive disorder (MDD) …
disorders. There are two major types of mood disorders: major depressive disorder (MDD) …
Exploring macroscopic fluctuation of facial expression for mood disorder classification
In clinical diagnosis of mood disorder, a large portion of bipolar disorder patients (BDs) are
misdiagnosed as unipolar depression (UDs). Clinicians have confirmed that BDs generally …
misdiagnosed as unipolar depression (UDs). Clinicians have confirmed that BDs generally …