ArticleDiagnostics (Basel, Switzerland)2022
Diagnosis of Depressive Disorder Model on Facial Expression Based on Fast R-CNN.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 47 citations in OpenAlex.
- Real-Time Emotion Recognition for Improving the Teaching-Learning Process: A Scoping Review.Journal of imaging · 2024Article
- Sensing emotional valence and arousal dynamics through automated facial action unit analysis.Scientific reports · 2024Article
- MoodCapture: Depression Detection Using In-the-Wild Smartphone Images.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024Article
- A Hybrid Learning-Architecture for Mental Disorder Detection Using Emotion Recognition.IEEE access : practical innovations, open solutions · 2024Article
- A systematic review on automated clinical depression diagnosis.Npj mental health research · 2023Review
- A Dynamic Probabilistic Model for Heterogeneous Data Fusion: A Pilot Case Study from Computer-Aided Detection of Depression.Brain sciences · 2023Article
- Ultrasound image-based deep learning to assist in diagnosing gross extrathyroidal extension thyroid cancer: a retrospective multicenter study.EClinicalMedicine · 2023Article
- Challenges for Artificial Intelligence in Recognizing Mental Disorders.Diagnostics (Basel, Switzerland) · 2022Review
- [A lightweight multiscale target object detection network for melanoma based on attention mechanism manipulation].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022Article
- Measuring depression severity based on facial expression and body movement using deep convolutional neural network.Frontiers in psychiatry · 2022Article
- Deep Learning-Based Mental Health Model on Primary and Secondary School Students' Quality Cultivation.Computational intelligence and neuroscience · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study examines related literature to propose a model based on artificial intelligence (AI), that can assist in the diagnosis of depressive disorder. Depressive disorder can be diagnosed through a self-report questionnaire, but it is necessary to check the mood and confirm the consistency of subjective and objective descriptions. Smartphone-based assistance in diagnosing depressive disorders can quickly lead to their identification and provide data for intervention provision. Through fast region-based convolutional neural networks (R-CNN), a deep learning method that recognizes vector-based information, a model to assist in the diagnosis of depressive disorder can be devised by checking the position change of the eyes and lips, and guessing emotions based on accumulated photos of the participants who will repeatedly participate in the diagnosis of depressive disorder.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.