Zobrazeno 1 - 10
of 1 039
pro vyhledávání: '"Depression Detection"'
Autor:
Bakir Hadzic, Parvez Mohammed, Michael Danner, Julia Ohse, Yihong Zhang, Youssef Shiban, Matthias Rätsch
Publikováno v:
SICE Journal of Control, Measurement, and System Integration, Vol 17, Iss 1, Pp 135-143 (2024)
One of the most underdiagnosed medical conditions worldwide is depression. It has been demonstrated that the current classical procedures for early detection of depression are insufficient, which emphasizes the importance of seeking a more efficient
Externí odkaz:
https://doaj.org/article/957d1148e02f40ba8681d4bc7791fe68
Autor:
Jithin Jacob, K.S. Kannan
Publikováno v:
Информатика и автоматизация, Vol 23, Iss 6, Pp 1754-1783 (2024)
Depression is a prevalent mental illness that requires autonomous detection systems due to its complexity. Existing machine learning techniques face challenges such as background noise sensitivity, slow adaptation speed, and imbalanced data. To addre
Externí odkaz:
https://doaj.org/article/848eb638dfeb463388e4b6361ce3a18b
Publikováno v:
Healthcare Technology Letters, Vol 11, Iss 4, Pp 218-226 (2024)
Abstract Depression is a serious mental state that negatively impacts thoughts, feelings, and actions. Social media use is rapidly growing, with people expressing themselves in their regional languages. In Pakistan and India, many people use Roman Ur
Externí odkaz:
https://doaj.org/article/714a08c0ede54f0eab6a9e47f01fc121
Publikováno v:
Frontiers in Computer Science, Vol 6 (2024)
This study aims to help in the area of depression screening in the Philippine setting, focusing on the detection of depression symptoms through language use and behavior in social media to help improve the accuracy of symptom tracking. A two-stage de
Externí odkaz:
https://doaj.org/article/793738b5e5764a768b09eeca6a88a942
Autor:
Shahid Munir Shah, Mahmoud Mohammad Aljawarneh, Muhammad Aamer Saleem, Mahmoud Saleh Jawarneh
Publikováno v:
PeerJ Computer Science, Vol 10, p e2296 (2024)
Mental illness is a common disease that at its extremes leads to personal and societal suffering. A complicated multi-factorial disease, mental illness is influenced by a number of socioeconomic and clinical factors, including individual risk factors
Externí odkaz:
https://doaj.org/article/42a04fbf148144bf9ecdbc8d05edf730
Publikováno v:
PeerJ Computer Science, Vol 10, p e2301 (2024)
Automated expert systems (AES) analyzing depression-related content on social media have piqued the interest of researchers. Depression, often linked to suicide, requires early prediction for potential life-saving interventions. In the conventional a
Externí odkaz:
https://doaj.org/article/7d73533cbeed476daf9d9421bbe341e0
Autor:
Wu, Yushan a, Zhong, Jitao a, Zhang, Lu a, Liu, Hele a, Shao, Shuai a, Hu, Bin a, c, d, e, Peng, Hong a, b, ⁎
Publikováno v:
In Neurocomputing 7 February 2025 617
Autor:
Prabhakar K, Kavitha V
Publikováno v:
Automatika, Vol 65, Iss 2, Pp 441-453 (2024)
One of the main factors causing suicide is depression. However, many cases of depression go undiagnosed because they are not correctly diagnosed. An increasing number of people with mental illnesses express their emotions online using tools like soci
Externí odkaz:
https://doaj.org/article/ef8beeff9feb491ebe2a18c204ea2ffe
Autor:
Marwa Hassan, Naima Kaabouch
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10532 (2024)
Major depressive disorder (MDD) poses a significant challenge in mental healthcare due to difficulties in accurate diagnosis and timely identification. This study explores the potential of machine learning models trained on EEG-based features for dep
Externí odkaz:
https://doaj.org/article/cbc37c7d137b4e92be28ae42a8e11152
Publikováno v:
Industrial Management & Data Systems, 2023, Vol. 123, Issue 12, pp. 3038-3052.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IMDS-12-2022-0754