A novel automated depression detection technique using text transcript
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22793
Abstract: Depression is one of the most common mental illnesses, impacting billions of people worldwide. The lack of existing resources is impeding the country's economic prosperity. As a result, new approaches for detecting and treating mental… read more here.
Keywords: automated depression; depression detection; depression; proposed approach ... See more keywords
Research on depression detection algorithm combine acoustic rhythm with sparse face recognition
Sign Up to like & getrecommendations! Published in 2017 at "Cluster Computing"
DOI: 10.1007/s10586-017-1469-0
Abstract: Due to the existence of false positive rate of the traditional depression diagnosis method, this paper proposes a multi-modal fusion algorithm based on speech signal and facial image sequence for depression diagnosis. Introduced spectrum subtraction… read more here.
Keywords: depression; recognition; rate; detection algorithm ... See more keywords
Depression detection from sMRI and rs-fMRI images using machine learning
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Intelligent Information Systems"
DOI: 10.1007/s10844-021-00653-w
Abstract: Major Depression Disorder (MDD) is a common mental disorder that negatively affects many people’s lives worldwide. Developing an automated method to find useful diagnostic biomarkers from brain imaging data would help clinicians to detect MDD… read more here.
Keywords: depression detection; machine learning; mri;
Depression detection from social network data using machine learning techniques
Sign Up to like & getrecommendations! Published in 2018 at "Health Information Science and Systems"
DOI: 10.1007/s13755-018-0046-0
Abstract: PurposeSocial networks have been developed as a great point for its users to communicate with their interested friends and share their opinions, photos, and videos reflecting their moods, feelings and sentiments. This creates an opportunity… read more here.
Keywords: depression; machine learning; social network; learning techniques ... See more keywords
Breaking Age Barriers With Automatic Voice-Based Depression Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Pervasive Computing"
DOI: 10.1109/mprv.2022.3163656
Abstract: Adults over the age of 60 years are a rising population at-risk for depression, and there is a need to create automatic screening for this illness. Most existing voice-based depression datasets comprise speakers younger than… read more here.
Keywords: depression detection; voice based; voice; age ... See more keywords
An Improved Classification Model for Depression Detection Using EEG and Eye Tracking Data
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on NanoBioscience"
DOI: 10.1109/tnb.2020.2990690
Abstract: At present, depression has become a main health burden in the world. However, there are many problems with the diagnosis of depression, such as low patient cooperation, subjective bias and low accuracy. Therefore, reliable and… read more here.
Keywords: depression detection; eye tracking; eeg eye; depression ... See more keywords
Adolescent Depression Detection Model Based on Multimodal Data of Interview Audio and Text
Sign Up to like & getrecommendations! Published in 2022 at "International journal of neural systems"
DOI: 10.1142/s0129065722500459
Abstract: 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 suicide. The establishment of the computer-aided model may… read more here.
Keywords: depression detection; depression; detection; detection model ... See more keywords
Psychological Analysis for Depression Detection from Social Networking Sites
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/4395358
Abstract: Rapid technological advancements are altering people's communication styles. With the growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have become popular forums for people to share their thoughts, psychological behavior, and emotions.… read more here.
Keywords: psychological analysis; social networks; depression detection; depression ... See more keywords
On the review of image and video-based depression detection using machine learning
Sign Up to like & getrecommendations! Published in 2020 at "Indonesian Journal of Electrical Engineering and Computer Science"
DOI: 10.11591/ijeecs.v19.i3.pp1677-1684
Abstract: Machine learning has been introduced in the sphere of the medical field to enhance the accuracy, precision, and analysis of diagnostics while reducing laborious jobs. With the mounting evidence, machine learning has the capability to… read more here.
Keywords: depression; image video; machine learning; depression detection ... See more keywords
Comparing Selective Masking Methods for Depression Detection in Social Media
Sign Up to like & getrecommendations! Published in 2023 at "Computational Linguistics"
DOI: 10.1162/coli_a_00479
Abstract: Identifying those at risk for depression is a crucial issue where social media provides an excellent platform for examining the linguistic patterns of depressed individuals. A significant challenge in depression classification problem is ensuring that… read more here.
Keywords: social media; selective masking; depression detection; depression ... See more keywords
Few-Electrode EEG from the Wearable Devices Using Domain Adaptation for Depression Detection
Sign Up to like & getrecommendations! Published in 2022 at "Biosensors"
DOI: 10.3390/bios12121087
Abstract: Nowadays, major depressive disorder (MDD) has become a crucial mental disease that endangers human health. Good results have been achieved by electroencephalogram (EEG) signals in the detection of depression. However, EEG signals are time-varying, and… read more here.
Keywords: domain adaptation; adaptation; eeg signals; depression detection ... See more keywords