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28/04/2023, 12:40 Aprendizagem profunda para reconhecimento de depressão com pistas audiovisuais: uma revisão - ScienceDirect https://www.sciencedirect.com/science/article/abs/pii/S1566253521002207 1/3 Fusão de informações volume 80, abril de 2022 , páginas 56-86 Aprendizagem profunda para reconhecimento de depressão com pistas audiovisuais: uma revisão Lang He ,Mingyue Niu ,Prayag Tiwari ,Pekka Martinen ,Rui Su , Jiewei Jiang ,Chenguang Guoi ,Hongyu Wang ,Songtao Ding ,Zhongmin Wang ,Xiaoying Pan ,Wei Dang Mostre mais Contorno https://doi.org/10.1016/j.inffus.2021.10.012 ↗ Obtenha direitos e conteúdo ↗ Destaques • Primeira revisão sobre o reconhecimento da depressão a partir de pistas audiovisuais que lida com análise modal única e multimodal. • A revisão enfoca o aprendizado profundo que está adotando na tarefa de reconhecimento de depressão com pistas audiovisuais. • Abrange os métodos de ponta para o reconhecimento de depressão em detalhes. Abstrato With the acceleration of the pace of work and life, people are facing more and more pressure, which increases the probability of suffering from depression. However, many patients may fail to get a timely diagnosis due to the serious imbalance in the doctor–patient ratio in the world. A promising development is that physiological and psychological studies have found some differences in speech and facial expression between patients with depression and healthy individuals. Consequently, to improve current medical care, Deep Learning (DL) has been used to extract a representation of depression cues from audio and video for automatic depression detection. To classify and summarize such research, we introduce the databases and describe objective markers for automatic depression estimation. We also review the DL methods for automatic detection of depression to extract a representation of depression from audio and video. Lastly, we discuss challenges and promising directions related to the automatic diagnoses of depression using DL. a b c d e f f g h _ a b a b ab _ a b j Compartilhar Citar https://www.sciencedirect.com/journal/information-fusion https://www.sciencedirect.com/journal/information-fusion/vol/80/suppl/C https://doi.org/10.1016/j.inffus.2021.10.012 https://s100.copyright.com/AppDispatchServlet?publisherName=ELS&contentID=S1566253521002207&orderBeanReset=true https://www.sciencedirect.com/topics/engineering/deep-learning https://www.sciencedirect.com/ 28/04/2023, 12:40 Aprendizagem profunda para reconhecimento de depressão com pistas audiovisuais: uma revisão - ScienceDirect https://www.sciencedirect.com/science/article/abs/pii/S1566253521002207 2/3 Previous Next Keywords Affective computing; Depression; Deep learning; Automatic depression estimation; Review Artigos recomendados Cited by (34) Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review 2023, Information Fusion Citation Excerpt : …The main objective of these screening methods is the early diagnosis of various brain diseases by specialists accurately [317,318]. Among the different proposed diagnosis methods, specialists prefer more neuroimaging modalities; hence, these methods are extensively used for diagnosing brain diseases [319–322]. Neuroimaging modalities provide essential information to physicians about the structure and function of the brain; therefore, they are popular among researchers and physicians for brain disease diagnosis [323–326].… Show abstract A multimodal fusion model with multi-level attention mechanism for depression detection 2023, Biomedical Signal Processing and Control Show abstract Depression recognition using a proposed speech chain model fusing speech production and perception features 2023, Journal of Affective Disorders Citation Excerpt : …With respect to auditory perception, the second dimension of the Mel-frequency cepstral coefficients (MFCC-2) of depressed patients was significantly higher than that of non-depressed subjects, which reflected an energy difference of frequencies around 2000–3000 Hz (Taguchi et al., 2018). Based on these differences, the MFCC, Mel-spectrogram, and spectrogram, which reflect time-frequency information, have been used in depression diagnosis and have shown positive performance (He et al., 2022; Rejaibi et al., 2022; Vázquez-Romero and Gallardo-Antolín, 2020; Yadav and Sharma, 2021). However, these features are extracted only from the speech perception process based on the sensory differences in how the depressive speech sounded rather than how it is produced.… Show abstract Modern views of machine learning for precision psychiatry 2022, Patterns https://www.sciencedirect.com/science/article/pii/S1566253521002190 https://www.sciencedirect.com/science/article/pii/S1566253521002256 https://www.sciencedirect.com/science/article/pii/S1566253522002573 https://www.sciencedirect.com/science/article/pii/S1746809422010151 https://www.sciencedirect.com/science/article/pii/S0165032722013209 https://www.sciencedirect.com/science/article/pii/S2666389922002276 28/04/2023, 12:40 Aprendizagem profunda para reconhecimento de depressão com pistas audiovisuais: uma revisão - ScienceDirect https://www.sciencedirect.com/science/article/abs/pii/S1566253521002207 3/3 Citation Excerpt : …This makes the ML models more applicable in augmenting human caregivers by bringing up a specific insight that they would like to measure. In depression studies, some approaches have also involved fusion of video features derived from each frame that are used to train a sequential DNN,201 and some have used pre-training to compensate a relatively small sample size of depression datasets.202 While these models perform very well on the same held-out test set, their clinical applications remain limited due to a lack of interpretability.… Show abstract A multimodal computer-aided diagnostic system for depression relapse prediction using audiovisual cues: A proof of concept 2022, Healthcare Analytics Show abstract A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data 2022, Métodos e programas de computador em biomedicina Citação Trecho: …Um mecanismo de atenção, bem como um agrupamento de pirâmide espacial ponderada (WSPP) são integrados em uma CNN para aprender uma representação facial profunda e global da depressão a partir de vídeos em [13]. Um artigo de pesquisa recente sobre métodos de aprendizado profundo para detecção automática de depressão para extrair a representação da depressão de áudio e vídeo é fornecido em [14]. Muitas abordagens focaram no uso de recursos de áudio para detecção de depressão por causa de sua eficiência, facilidade de aquisição e proteção da privacidade dos pacientes.… Mostrar resumo Veja todos os artigos de citação no Scopus Ver texto completo © 2021 Elsevier BV Todos os direitos reservados. Copyright © 2023 Elsevier BV ou seus licenciadores ou colaboradores. ScienceDirect® is a registered trademark of Elsevier B.V. https://www.sciencedirect.com/science/article/pii/S2772442522000387 https://www.sciencedirect.com/science/article/pii/S0169260722005132 http://www.scopus.com/scopus/inward/citedby.url?partnerID=10&rel=3.0.0&eid=2-s2.0-85119410378&md5=f4a75e2ebc435255fc152d3e4b7320a https://www.sciencedirect.com/science/article/pii/S1566253521002207 https://www.elsevier.com/ https://www.relx.com/