Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions
Sentiment analysis (SA) has gained much traction In the field of artificial intelligence (AI) and
natural language processing (NLP). There is growing demand to automate analysis of user …
natural language processing (NLP). There is growing demand to automate analysis of user …
[HTML][HTML] Bio-acoustic features of depression: A review
SA Almaghrabi, SR Clark, M Baumert - Biomedical Signal Processing and …, 2023 - Elsevier
Speech carries essential information about the speaker's physiology and possible
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
Depression screening in humans with AI and deep learning techniques
Social media platforms have been widely used as a communication tool where most of the
population expresses their feelings and shares life experiences. Along with general …
population expresses their feelings and shares life experiences. Along with general …
Multimodal sentiment analysis: A survey
S Lai, X Hu, H Xu, Z Ren, Z Liu - Displays, 2023 - Elsevier
Multimodal sentiment analysis has emerged as a prominent research field within artificial
intelligence, benefiting immensely from recent advancements in deep learning. This …
intelligence, benefiting immensely from recent advancements in deep learning. This …
A multimodal approach for mania level prediction in bipolar disorder
Bipolar disorder is a mental health disorder that causes mood swings that range from
depression to mania. Clinical diagnosis of bipolar disorder is based on patient interviews …
depression to mania. Clinical diagnosis of bipolar disorder is based on patient interviews …
Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms
Depression is a serious mental health condition that affects a person's ability to feel happy
and engaged in activities. The COVID-19 pandemic has led to an increase in depression …
and engaged in activities. The COVID-19 pandemic has led to an increase in depression …
Applications of speech analysis in psychiatry
K Dikaios, S Rempel, SH Dumpala… - Harvard Review of …, 2023 - journals.lww.com
The need for objective measurement in psychiatry has stimulated interest in alternative
indicators of the presence and severity of illness. Speech may offer a source of information …
indicators of the presence and severity of illness. Speech may offer a source of information …
Adolescent depression detection model based on multimodal data of interview audio and text
Depression is a common mental disease that has a tendency to develop at a younger age.
Early detection of depression with psychological intervention may effectively prevent youth …
Early detection of depression with psychological intervention may effectively prevent youth …
A systematic review on automated clinical depression diagnosis
Assessing mental health disorders and determining treatment can be difficult for a number of
reasons, including access to healthcare providers. Assessments and treatments may not be …
reasons, including access to healthcare providers. Assessments and treatments may not be …