Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (96)
  • Open Access

    ARTICLE

    Deep Learning for Depression Detection Using Twitter Data

    Doaa Sami Khafaga1, Maheshwari Auvdaiappan2, K. Deepa3, Mohamed Abouhawwash4,5, Faten Khalid Karim1,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1301-1313, 2023, DOI:10.32604/iasc.2023.033360 - 05 January 2023

    Abstract Today social media became a communication line among people to share their happiness, sadness, and anger with their end-users. It is necessary to know people’s emotions are very important to identify depressed people from their messages. Early depression detection helps to save people’s lives and other dangerous mental diseases. There are many intelligent algorithms for predicting depression with high accuracy, but they lack the definition of such cases. Several machine learning methods help to identify depressed people. But the accuracy of existing methods was not satisfactory. To overcome this issue, the deep learning method is… More >

  • Open Access

    ARTICLE

    EliteVec: Feature Fusion for Depression Diagnosis Using Optimized Long Short-Term Memory Network

    S. Kavi Priya*, K. Pon Karthika

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1745-1766, 2023, DOI:10.32604/iasc.2023.032160 - 05 January 2023

    Abstract Globally, depression is perceived as the most recurrent and risky disorder among young people and adults under the age of 60. Depression has a strong influence on the usage of words which can be observed in the form of written texts or stories posted on social media. With the help of Natural Language Processing(NLP) and Machine Learning (ML) techniques, the depressive signs expressed by people can be identified at the earliest stage from their Social Media posts. The proposed work aims to introduce an efficacious depression detection model unifying an exemplary feature extraction scheme and… More >

  • Open Access

    ARTICLE

    Predicting and Curing Depression Using Long Short Term Memory and Global Vector

    Ayan Kumar1, Abdul Quadir Md1, J. Christy Jackson1,*, Celestine Iwendi2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5837-5852, 2023, DOI:10.32604/cmc.2023.033431 - 28 December 2022

    Abstract In today’s world, there are many people suffering from mental health problems such as depression and anxiety. If these conditions are not identified and treated early, they can get worse quickly and have far-reaching negative effects. Unfortunately, many people suffering from these conditions, especially depression and hypertension, are unaware of their existence until the conditions become chronic. Thus, this paper proposes a novel approach using Bi-directional Long Short-Term Memory (Bi-LSTM) algorithm and Global Vector (GloVe) algorithm for the prediction and treatment of these conditions. Smartwatches and fitness bands can be equipped with these algorithms which… More >

  • Open Access

    ARTICLE

    Cross-Sectional Associations of Lifestyle Behaviors with Depressive Symptoms in Adolescents

    Weiman Kong1, Jiayi Gu2,*

    International Journal of Mental Health Promotion, Vol.25, No.1, pp. 139-152, 2023, DOI:10.32604/ijmhp.2022.022123 - 29 November 2022

    Abstract This study aimed to examine the associations between lifestyle behaviors and depressive symptoms in adolescents. Self-reported data from the 2019 Youth Risk Behavior Survey (YRBS) was analyzed. Depressive symptoms were set as the outcome variable. Movement variables (physical activity, muscle-strengthening exercise, physical education attendance, sports team participation, television watching, video or computer games, and sleep), eating behaviors (fruit intake, vegetable intake, milk intake, and eating breakfast or not), and substance use (alcohol use and cigarette use) were included as explanatory variables. Binary logistic regression was used to explore the associations between lifestyle behaviors and depressive… More >

  • Open Access

    ARTICLE

    The relationship of depression, alcohol and marijuana with treatment for LUTS/BPH

    Granville L. Lloyd1, Alan M. Makedon1, Jeffrey M. Marks2, Brett Wiesen1, Heather Carmichael1

    Canadian Journal of Urology, Vol.29, No.4, pp. 11249-11254, 2022

    Abstract Introduction: Despite widespread usage, research on the relationship of marijuana use to disease is sorely lacking. We sought to test the relationship of LUTS/BPH treatment and endocannabinoid agonist usage, as well as alcohol usage and depression, with treatment for LUTS/BPH in our health system.
    Materials and methods: We queried our hospital system database of nearly three million patients in a marijuana-legalized region for data from the electronic medical record between January 2011 and October 2018. Men over the age of 45 on medical therapy for LUTS (selective alpha blockade and/or finasteride) were included. Exclusions were diagnosis of… More >

  • Open Access

    ARTICLE

    Méditation de pleine conscience pour les patients en oncologie : adapter la pratique en temps de pandémie

    A. Couillet, B. Mastroianni, J. Hailloud, M.-P. Le Bris, G. Chvetzoff

    Psycho-Oncologie, Vol.16, No.1, pp. 182-191, 2022, DOI:10.3166/pson-2022-0183

    Abstract Des ateliers de méditation ont été proposés aux patients, nous en avons étudié la faisabilité pendant les soins oncologiques. Ils ont été adaptés du fait de la Covid-19 : une session a eu lieu en présentiel, la suivante en distanciel. Les données ont été analysées de manière rétrospective. Une analyse mixte a été menée : le volet quantitatif a évalué la participation aux ateliers, les caractéristiques des patients et l’impact des ateliers, le volet qualitatif s’est concentré sur l’appropriation de cet outil par les patients. Concernant la faisabilité, 66,7 % des patients ont terminé le More >

  • Open Access

    ARTICLE

    Effects of Health Qigong Exercise on Depression and Anxiety in Patients with Parkinson’s Disease

    Xiying Li1, Alyx Taylor2, Jinming Li3, Ting Wang3, Jing Kuang3, Zhihao Zhang3, Xiaolei Liu4, Tingting Liu4, Xia Qin5, Shenghua Lu6,7,*, Liye Zou3

    International Journal of Mental Health Promotion, Vol.24, No.6, pp. 855-867, 2022, DOI:10.32604/ijmhp.2022.021508 - 28 September 2022

    Abstract Objective: This study explored the effects of Health Qigong exercise on depression and anxiety in patients with Parkinson’s disease (PD). Methods: A total of 42 volunteers who met the inclusion criteria were recruited and randomly allocated into the experimental group and the control group. The experimental group carried out 60-minute sessions of Health Qigong exercise five times a week for 12 weeks while the control group did not perform any regular physical exercise. Data on cognitive impairment, psychomotor retardation, somatic anxiety, weight loss and sleep disorders, the sum score of the 17-item Hamilton Depression Rating Scale (HDRS-17), More >

  • Open Access

    ARTICLE

    Emotions, Perceptions and Health Behaviors of Adult Congenital Heart Disease Patients during COVID-19 in New York City

    Jodi L. Feinberg1, Peter Sheng2, Stephanie Pena2, Adam J. Small1, Susanna Wendelboe1, Katlyn Nemani3, Vikram Agrawal4, Dan G. Halpern1,*

    Congenital Heart Disease, Vol.17, No.5, pp. 519-531, 2022, DOI:10.32604/chd.2022.024174 - 06 September 2022

    Abstract Background: Adults with congenital heart disease (ACHD) have increased prevalence of mood and anxiety disorders. There are limited data regarding the influence of the COVID-19 pandemic on the mental health and health behaviors of these patients. Objective: The purpose is to evaluate the perceptions, emotions, and health behaviors of ACHD patients during the COVID-19 pandemic. Methods: In this cross-sectional study of ACHD patients, we administered surveys evaluating self-reported emotions, perceptions and health behaviors. Logistic regressions were performed to determine the adjusted odds of displaying each perception, emotion and health behavior based on predictor variables. Results: Ninety-seven patients… More > Graphic Abstract

    Emotions, Perceptions and Health Behaviors of Adult Congenital Heart Disease Patients during COVID-19 in New York City

  • Open Access

    ARTICLE

    Risk Factors and Gender Differences for Depression in Chilean Older Adults: A Cross-Sectional Analysis from the National Health Survey 2016–2017

    Gabriela Nazar1,2,*, Carlos-María Alcover3, Yeny Concha-Cisternas4,5, Igor Cigarroa5, Ximena Díaz-Martínez6, Mariela Gatica-Saavedra7, Fabián Lanuza8,9, Ana María Leiva-Ordónez10, María Adela Martínez-Sanguinetti11, Miquel Martorell2,12, Fanny Petermann-Rocha13,14, Claudia Troncoso-Pantoja15, Carlos Celis-Morales16

    International Journal of Mental Health Promotion, Vol.24, No.5, pp. 679-697, 2022, DOI:10.32604/ijmhp.2022.020105 - 27 July 2022

    Abstract Depressive disorders are recognized as one of the most common mental health conditions across different age groups. However, the risk factors associated with depression among older people from low-and middle-income countries remains unclear. This study aims to identify socio-demographic, health and psychosocial-related factors associated with depression in Chilean older adults. A cross-sectional study was carried out in a representative sample of 1,765 adults aged ≥60 years participants from the Chilean National Health Survey 2016–2017. Depression was assessed with the Composite International Diagnostic Interview (CIDI-SF). Associations between the exposure variables and depression were investigated using Poisson… More >

  • Open Access

    ARTICLE

    Physical exercise, Sedentary Behaviour, Sleep and Depression Symptoms in Chinese Young Adults During the COVID-19 Pandemic: A Compositional Isotemporal Analysis

    Jianjun Su1, Enxiu Wei1, Cain Clark2, Kaixin Liang3, Xiaojiao Sun4,*

    International Journal of Mental Health Promotion, Vol.24, No.5, pp. 759-769, 2022, DOI:10.32604/ijmhp.2022.020152 - 27 July 2022

    Abstract Numerous studies links movement activity (e.g., physical activity, sedentary behavior [SB], and sleep) with mental health or illness indicators during the COVID-19 pandemic; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This cross-sectional study aimed to use compositional isotemporal analysis to estimate the association between reallocation of time-use behaviors and depression symptoms in young adults in China. Participants (n = 1475; 68.0% of female; 20.7 [1.60] years) reported their time spent in moderate to vigorous physical activity (MVPA), light physical activity (LPA), SB, and sleep.… More >

Displaying 51-60 on page 6 of 96. Per Page