BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

249 related articles for article (PubMed ID: 37223978)

  • 1. Prediction of Diagnosis and Treatment Response in Adolescents With Depression by Using a Smartphone App and Deep Learning Approaches: Usability Study.
    Kim JS; Wang B; Kim M; Lee J; Kim H; Roh D; Lee KH; Hong SB; Lim JS; Kim JW; Ryan N
    JMIR Form Res; 2023 May; 7():e45991. PubMed ID: 37223978
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Tracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study.
    Cao J; Truong AL; Banu S; Shah AA; Sabharwal A; Moukaddam N
    JMIR Ment Health; 2020 Jan; 7(1):e14045. PubMed ID: 32012072
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Behavioral and Self-reported Data Collected From Smartphones for the Assessment of Depressive and Manic Symptoms in Patients With Bipolar Disorder: Prospective Observational Study.
    Dominiak M; Kaczmarek-Majer K; Antosik-Wójcińska AZ; Opara KR; Olwert A; Radziszewska W; Hryniewicz O; Święcicki Ł; Wojnar M; Mierzejewski P
    J Med Internet Res; 2022 Jan; 24(1):e28647. PubMed ID: 34874015
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Personality traits predict treatment outcome of an antidepressant in untreated adolescents with depression: An 8-week, open-label, flexible-dose study.
    Ran LY; Liu XY; Wang W; Tao WQ; Xiang JJ; Zeng Q; Kong YT; Zhang CY; Liao J; Qiu HT; Kuang L
    J Affect Disord; 2024 Apr; 350():102-109. PubMed ID: 38199422
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Early changes of serum BDNF and SSRI response in adolescents with major depressive disorder.
    Lee J; Lee KH; Kim SH; Han JY; Hong SB; Cho SC; Kim JW; Brent D
    J Affect Disord; 2020 Mar; 265():325-332. PubMed ID: 32090756
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach.
    Kim AY; Jang EH; Lee SH; Choi KY; Park JG; Shin HC
    J Med Internet Res; 2023 Jan; 25():e34474. PubMed ID: 36696160
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning-Based Exploratory Study.
    Mullick T; Radovic A; Shaaban S; Doryab A
    JMIR Form Res; 2022 Jun; 6(6):e35807. PubMed ID: 35749157
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study.
    Maleki G; Zhuparris A; Koopmans I; Doll RJ; Voet N; Cohen A; van Brummelen E; Groeneveld GJ; De Maeyer J
    JMIR Form Res; 2022 Sep; 6(9):e31775. PubMed ID: 36098990
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Tracking and Monitoring Mood Stability of Patients With Major Depressive Disorder by Machine Learning Models Using Passive Digital Data: Prospective Naturalistic Multicenter Study.
    Bai R; Xiao L; Guo Y; Zhu X; Li N; Wang Y; Chen Q; Feng L; Wang Y; Yu X; Xie H; Wang G
    JMIR Mhealth Uhealth; 2021 Mar; 9(3):e24365. PubMed ID: 33683207
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study.
    Opoku Asare K; Terhorst Y; Vega J; Peltonen E; Lagerspetz E; Ferreira D
    JMIR Mhealth Uhealth; 2021 Jul; 9(7):e26540. PubMed ID: 34255713
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Toward a Mobile Platform for Real-world Digital Measurement of Depression: User-Centered Design, Data Quality, and Behavioral and Clinical Modeling.
    Nickels S; Edwards MD; Poole SF; Winter D; Gronsbell J; Rozenkrants B; Miller DP; Fleck M; McLean A; Peterson B; Chen Y; Hwang A; Rust-Smith D; Brant A; Campbell A; Chen C; Walter C; Arean PA; Hsin H; Myers LJ; Marks WJ; Mega JL; Schlosser DA; Conrad AJ; Califf RM; Fromer M
    JMIR Ment Health; 2021 Aug; 8(8):e27589. PubMed ID: 34383685
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reducing depressive symptomatology with a smartphone app: study protocol for a randomized, placebo-controlled trial.
    Giosan C; Cobeanu O; Mogoaşe C; Szentagotai A; Mureşan V; Boian R
    Trials; 2017 May; 18(1):215. PubMed ID: 28494802
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Psychometric Properties and Factor Structures of the Korean Version of Children's Depression Rating Scale-Revised.
    Kim KM; Nam S; Choi JW; Jung AH; Hong SB; Kim JW; Kim SY; Kim E; Kim JW
    J Child Adolesc Psychopharmacol; 2018 May; 28(4):285-292. PubMed ID: 28771381
    [TBL] [Abstract][Full Text] [Related]  

  • 14. [Selective serotonin reuptake inhibitors in major depressive disorder in children and adolescents (ratio of benefits/risks)].
    Hjalmarsson L; Corcos M; Jeammet P
    Encephale; 2005; 31(3):309-16. PubMed ID: 16142045
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Smartphone Cognitive Behavioral Therapy as an Adjunct to Pharmacotherapy for Refractory Depression: Randomized Controlled Trial.
    Mantani A; Kato T; Furukawa TA; Horikoshi M; Imai H; Hiroe T; Chino B; Funayama T; Yonemoto N; Zhou Q; Kawanishi N
    J Med Internet Res; 2017 Nov; 19(11):e373. PubMed ID: 29101095
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Machine Learning Approach for Detecting Digital Behavioral Patterns of Depression Using Nonintrusive Smartphone Data (Complementary Path to Patient Health Questionnaire-9 Assessment): Prospective Observational Study.
    Choudhary S; Thomas N; Ellenberger J; Srinivasan G; Cohen R
    JMIR Form Res; 2022 May; 6(5):e37736. PubMed ID: 35420993
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.
    Sun S; Folarin AA; Zhang Y; Cummins N; Garcia-Dias R; Stewart C; Ranjan Y; Rashid Z; Conde P; Laiou P; Sankesara H; Matcham F; Leightley D; White KM; Oetzmann C; Ivan A; Lamers F; Siddi S; Simblett S; Nica R; Rintala A; Mohr DC; Myin-Germeys I; Wykes T; Haro JM; Penninx BWJH; Vairavan S; Narayan VA; Annas P; Hotopf M; Dobson RJB;
    J Med Internet Res; 2023 Aug; 25():e45233. PubMed ID: 37578823
    [TBL] [Abstract][Full Text] [Related]  

  • 18. New generation antidepressants for depression in children and adolescents: a network meta-analysis.
    Hetrick SE; McKenzie JE; Bailey AP; Sharma V; Moller CI; Badcock PB; Cox GR; Merry SN; Meader N
    Cochrane Database Syst Rev; 2021 May; 5(5):CD013674. PubMed ID: 34029378
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Examining the Correlation Between Depression and Social Behavior on Smartphones Through Usage Metadata: Empirical Study.
    Wang Y; Ren X; Liu X; Zhu T
    JMIR Mhealth Uhealth; 2021 Jan; 9(1):e19046. PubMed ID: 33404512
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Formative Evaluation of a Smartphone App for Monitoring Daily Meal Distribution and Food Selection in Adolescents: Acceptability and Usability Study.
    Langlet B; Maramis C; Diou C; Maglaveras N; Fagerberg P; Heimeier R; Lekka I; Delopoulos A; Ioakimidis I
    JMIR Mhealth Uhealth; 2020 Jul; 8(7):e14778. PubMed ID: 32706684
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.