AIMC Topic: Depression

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[A research on depression recognition based on voice pre-training model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
For the increasing number of patients with depression, this paper proposes an artificial intelligence method to effectively identify depression through voice signals, with the aim of improving the efficiency of diagnosis and treatment. Firstly, a pre...

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

International journal of geriatric psychiatry
BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associated with the onset of dementia. Currently, the diagnosis of geriatric depression and anxiety relies on self-reported assessments for primary screening...

Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

AMIA ... Annual Symposium proceedings. AMIA Symposium
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) models in a retrospective cohort study with a large sample size. We analyzed the association between depr...

Navigating the Intersection of Technology and Depression Precision Medicine.

Advances in experimental medicine and biology
This chapter primarily focuses on the progress in depression precision medicine with specific emphasis on the integrative approaches that include artificial intelligence and other data, tools, and technologies. After the description of the concept of...

[A preliminary prediction model of depression based on whole blood cell count by machine learning method].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter stu...

Neuronetwork Approach in the Early Diagnosis of Depression.

Psychiatria Danubina
BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the pa...

Deep Depression Detection with Resting-State and Cognitive-Task EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Depression is a common mental disorder that negatively affects physical health and personal, social and occupational functioning. Currently, accurate and objective diagnosis of depression remains challenging, and electroencephalography (EEG) provides...

Performance of Artificial Intelligence in Predicting Future Depression Levels.

Studies in health technology and informatics
Depression is a prevalent mental condition that is challenging to diagnose using conventional techniques. Using machine learning and deep learning models with motor activity data, wearable AI technology has shown promise in reliably and effectively i...