이헌정 프로필 사진

이헌정

Lee, Heon Jeong
Web Of Science Scopus ORCID

자료 필터

자료유형

발행연도

1996 ~ 2027
1996 2027

키워드

언어

전체 526건 중 11번부터 20번까지의 결과를 표시합니다.

2026
Article

Genome-wide association study and polygenic risk score analysis for bipolar disorder in the Korean population

  • Choi, Min Jun ; 
  • Kim, Yujin ; 
  • Lee, Heon-Jeong ; 
  • Joo, Eun-Jeong ; 
  • Ahn, Yong Min ; 
  • 외 14명
  • 2026-08
  • Asian Journal of Psychiatry
  • Elsevier BV
Article

Mixed Features in Recurrent Major Depressive Disorder: Prevalence, Risk Factors, and Clinical Consequences

  • Park, C. Hyung Keun ; 
  • Park, Chanhee ; 
  • Rhee, Sang Jin ; 
  • Min, Sooyeon ; 
  • Song, Yoojin ; 
  • ... Lee, Heon-Jeong ; 
  • ... Ko, Young-Hoon ; 
  • 외 21명
  • 2026-08
  • Depression and Anxiety
  • John Wiley & Sons Inc.
Article

Network Analysis of Sleep, Mental Health, and Stress in Korean Dentists

  • 2026-08
  • International Dental Journal
  • FDI World Dental Press Ltd.
Article

Smartphone-Based Digital Phenotyping for Identifying Elevated Depressive Symptom Levels Using Machine Learning

  • 2026-07
  • Applied Sciences (Switzerland)
  • Multidisciplinary Digital Publishing Institute (MDPI)
Article

Interactive virtual reality exposure therapy vs metaphor-based VR for social anxiety disorder: Protocol for an active-comparator randomized trial with digital phenotyping

  • 2026-07
  • Digital Health
  • SAGE Publications
Article

Friend and Confidant Thresholds: Social Network Size as a Mediator Between Marital Status and Major Depressive Disorder

  • 2026-07
  • Depression and Anxiety
  • John Wiley & Sons Inc.
Article

Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings

  • 2026-06
  • Internet Interventions
  • Elsevier BV
Article

Is Sleep Enough? Why Circadian Rhythm Matters Beyond Sleep Duration

  • 2026-06
  • Chronobiology in Medicine
  • Korean Academy of Sleep Medicine
Article

Heart rate circadian phase and hyperarousal as wearable digital phenotyping of insomnia: An interpretable machine learning study

  • 2026-06
  • Digital Health
  • SAGE Publications