AIMC Topic: Anxiety
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Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.
International journal of medical informatics
Jan 22, 2025
BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogen...
Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.
Medicina (Kaunas, Lithuania)
Jan 22, 2025
: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on individuals' psychological states. Utilizing statistical methods and machine learning models, these studi...
Brain mapping, biomarker identification and using machine learning method for diagnosis of anxiety during emotional face in preschool children.
Brain research bulletin
Jan 9, 2025
BACKGROUND: Due to the importance and the consequences of anxiety, the goals of the current study are brain mapping, biomarker identification and the use of an assessment method for diagnosis of anxiety during emotional face in preschool children.
Prediction of health anxiety using resting-state functional near-infrared spectroscopy and machine learning.
Journal of affective disorders
Jan 8, 2025
BACKGROUND: The role of cortical networks in health anxiety remain poorly understood. This study aimed to develop a predictive model for health anxiety, using a machine-learning approach based on resting-state functional connectivity (rsFC) with func...
Research on the self-efficacy and resilience of female graduate students in the era of artificial intelligence: analysis of the mechanism of mobile phone dependence, anxiety and mentoring relationship.
Archives of women's mental health
Jan 7, 2025
PURPOSE: The purpose of this study is to investigate the impact of the employment situation on the anxiety levels and research self-efficacy of graduate students, with a particular focus on female graduate students. The study aims to understand how t...
Beyond the hot flashes: how machine learning is uncovering the complexity of menopause-related depression.
CNS spectrums
Jan 6, 2025
BACKGROUND: The transition into menopause marks a significant stage in a woman's life, indicating the end of reproductive capability. This period, encompassing perimenopause and menopause, is characterized by declining levels of estrogen and progeste...
Personalized stress optimization intervention to reduce adolescents' anxiety: A randomized controlled trial leveraging machine learning.
Journal of anxiety disorders
Jan 3, 2025
Anxiety symptoms are among the most prevalent mental health disorders in adolescents, highlighting the need for scalable and accessible interventions. As anxiety often co-occurs with perceived stress during adolescence, stress interventions may offer...
Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.
Biosensors
Jan 2, 2025
This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals undertaking rapid tests for SARS-CoV-2. To this end, a galvanic skin response (GSR) sensor that was connect...
Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice.
Journal of neurophysiology
Dec 30, 2024
Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, ...
Anxiety about artificial intelligence from patient and doctor-physician.
Patient education and counseling
Dec 22, 2024
OBJECTIVE: This paper investigates the anxiety surrounding the integration of artificial intelligence (AI) in doctor-patient interactions, analyzing the perspectives of both patients and healthcare providers to identify key concerns and potential sol...
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