음성과 텍스트를 이용하여 우울증 및 자살 위험을 평가하는 인공지능 기반 임상의사결정지원시스템에 관한 연구 = A study on artificial intelligence-based clinical decision support system to evaluate depression and suicide risk using voice and text

신다운 2022년
논문상세정보
' 음성과 텍스트를 이용하여 우울증 및 자살 위험을 평가하는 인공지능 기반 임상의사결정지원시스템에 관한 연구 = A study on artificial intelligence-based clinical decision support system to evaluate depression and suicide risk using voice and text' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 의료과학 약
  • 기계학습
  • 목소리
  • 우울증
  • 임상의사결정지원시스템
  • 자살위험
  • 텍스트
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
5,885 0

0.0%

' 음성과 텍스트를 이용하여 우울증 및 자살 위험을 평가하는 인공지능 기반 임상의사결정지원시스템에 관한 연구 = A study on artificial intelligence-based clinical decision support system to evaluate depression and suicide risk using voice and text' 의 참고문헌

  • 텍스트 및 영상의 멀티모달분석을 이용한 트위터 사용자의 감성 흐름 모니터링 기술
    고은정 김은이 한국융합학회논문지, 9(1), 419-431 [2018]
  • 자살 위험성이 높은 청소년을 대상으로 한 우울중재 및 자살예방 프로그램의 효과
    남민선 손정우 유재순 지역사회간호학회지, 21(1), 71-81 [2010]
  • 우울증 화자 음성의 음향음성학적 특징
    백연숙 한국음성학회 , 4권 1호, p. 91~98 [2012]
  • assessment instruments : evaluation and recommendations
  • `` Linear vs. quadratic discriminant analysis classifier : a tutorial .
    Tharwat , Alaa 3 ( 2 ) : 145. doi:10.1504/IJAPR.2016.079050 . ISSN 2049-887X . [2016]
  • `` Cultural Stigma Manifested in Official Suicide Death in South Korea
    Im , J. S. , et al . 77 ( 4 ) : 386- 403 [2018]
  • Vocal affect expression : a review and a model for future research
    Scherer , K. R. 99 ( 2 ) , 143 . [1986]
  • Verbal indicators of depression
    Breznitz , Z 119 ( 4 ) , 351-363 . [1992]
  • Triaging suicidal patients : sifting through the evidence
    D. E. Clarke , A.-M. Brown , and L. Giles-Smith vol . 16 , no . 3 , pp . 165 ? 174 [2008]
  • Toward the future of psychiatric diagnosis : the seven pillars of RDoC
  • The underrecognition and undertreatment of depression : what is the breadth and depth of the problem ?
    Davidson , J.R. and S.E . Meltzer-Brody 60 ( 7 ) : p. 4-11 . [1999]
  • The measurement of suicidal ideation .
    Watson , D. , et al. , 22 ( 1 ) : p. 12-4 . [2001]
  • The increasing burden of depression .
    Lepine , J.P. and M. Briley 7 ( Suppl 1 ) : p. 3-7 . [2011]
  • The content of suicide notes from attempters and completers .
    Handelman , L.D . and D. Lester , 28 ( 2 ) : p. 102-4 . [2007]
  • The Psychiatric Interview
    Sullivan , H.S. 14 ( 4 ) : p. 361-373 . [1951]
  • The PHQ-9 : Validity of a brief depression severity measure
  • Suicide in manic depressive illness
    Jamison , K. and F. Goodwin , p. 157-173 . [1990]
  • Suicide as escape from self
    Baumeister , R. F. 97 ( 1 ) , 90 . [1990]
  • Sensitivity , specificity , and predictive values : foundations , pliabilities , and pitfalls in research and practice
    Trevethan , R. 5 , 307 [2017]
  • S. Clinical diagnosis of depression in primary care : A meta-analysis
    Mitchell , A.J . ; Vaze , A. ; Rao 374 , 609 ? 619 , doi:10.1016/s0140-6736 ( 09 ) 60879-5 . [2009]
  • Rule , Confidence intervals
    Ci , B. and R.-O . 1 ( 8531 ) : p. 494-7 . [1987]
  • Relationship between the Beck Anxiety Inventory and the Hamilton Anxiety Rating-Scale with Anxious Outpatients .
    Beck , A.T. ; Steer , R.A 5 , 213 ? 223 [1991]
  • Relationship between 5-HT function and impulsivity and aggression in male offenders with personality disorders
  • Relations between muscular tension and performance
    Courts , F. A . 39 ( 6 ) , 347 . [1942]
  • Recognition of audio depression based on convolutional neural network and generative antagonism network model
  • Psychometric Meta- Analysis of the English Version of the Beck Anxiety Inventory
    Bardhoshi , G. ; Duncan , K. ; Erford , B.T 94 , 356 ? 373 , doi:10.1002/jcad.12090 . [2016]
  • Progressive muscle relaxation .
  • Prevalence of major depressive disorder in the general population of South Korea
    Ohayon MM , Hong SC 40 ( 1 ) :30 ? 6 [2006]
  • Predictors of Effect of Atypical Antipsychotics on Speech .
    Sinha , P. , et al. 37 ( 4 ) : p. 429-33 . [2015]
  • Perception of atypical antipsychotics ' side effects through speech analysis of schizophrenic patients . TALK Study ]
    Bouloudnine , S. , et al. , 37 Suppl 2 : p. S143-50 . [2011]
  • Overview of artificial intelligence in medicine
  • Normality tests for statistical analysis : a guide for non-statisticians
    Ghasemi , A. and S. Zahediasl 10 ( 2 ) : p. 486 . [2012]
  • Minor depressive disorder and subsyndromal depressive symptoms : Functional impairment and response to treatment
    Rapaport , M.H . ; Judd , L.L 48 , 227 ? 232 [1998]
  • Impulsivity : a state as well as trait variable . Does mood awareness explain low correlations between trait and behavioural measures of impulsivity ?
    Wingrove , J. , & Bond , A. J . 22 ( 3 ) , 333- 339 . [1997]
  • Factor analysis of some psychometric measures of impulsiveness and anxiety
    Barratt , E. S. 16 ( 2 ) , 547-554 . [1965]
  • Elongation of pause-time in speech : a simple , objective measure of motor retardation in depression
  • Effect of Hormonal Replacement Therapy on Voice .
    Hamdan , A.L. , et al. , 32 ( 1 ) : p. 116-121 . [2018]
  • Economic burden of depression in South Korea .
    Chang SM , Hong JP , Cho MJ . 47 ( 5 ) :683 ? 9 . [2012]
  • Detection of the Optimum Spectral Roll-off Point using Violin as a Sound Source
    Kim , J.-C 12 , 51 ? 56 [2007]
  • Detection of clinical depression in adolescents ' speech during family interactions
    Low , L.S. , et al. 58 ( 3 ) : p. 574-86 [2011]
  • Depression and suicide
    Jeon HJ 54:370-375 [2011]
  • Depression and other common mental disorders : Global health estimates
    WHO 1- 24 [2017]
  • Clinical decision support systems in psychiatry in the information age
    Kotze , B. , & Brdaroska , B . 12 ( 4 ) , 361-364 . [2004]
  • Characteristics and psychosocial problems of patients with bipolar disorder at high risk for suicide attempt
  • Automated depression analysis using convolutional neural networks from speech
    He , L. , & Cao , C. 83 , 103-111 . [2018]
  • Assessment of suicidality in a Moroccan metropolitan area
  • Assessment of suicidal intention : the Scale for Suicide Ideation
  • Assessing the risk of suicide at triage ,
    N. Sands vol . 10 , no . 4 , pp . 161 ? 163 [2007]
  • Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies . Sankhy ?
    Mardia , K.V 115 ? 128 [1974]
  • Anxiety and depression in speech
    Pope , B. , et al. 35 ( 1 ) : p. 128-33 . [1970]
  • Adaptive boosting for SAR automatic target recognition
  • Accuracy of Patient Health Questionnaire-9 ( PHQ-9 ) for screening to detect major depression : Individual participant data meta-analysis
    Levis , B. ; Benedetti , A. ; Thombs , B.D . 365 , l1476 , doi:10.1136/bmj.l1476 . [2019]
  • A new statistic for testing for normality .
    Tiku , M. 3 ( 3 ) : p. 223-232 . [1974]
  • 99. Nilsonne, Å.; Sundberg, J.; Ternström, S.; Askenfelt, A. Measuring the rate of change of voice fundamental frequency in fluent speech during mental depression. J. Acoust. Soc. Am. 1988, 83, 716–728.
    [1988]
  • 98. Taguchi, T.; Tachikawa, H.; Nemoto, K.; Suzuki, M.; Nagano, T.; Tachibana, R.; Nishimura, M.; Arai, T. Major depressive disorder discrimination using vocal acoustic features. J. Affect. Disord. 2018, 225, 214–220.
    [2018]
  • 97. Wang, J.; Zhang, L.; Liu, T.; Pan, W.; Hu, B.; Zhu, T. Acoustic differences between healthy and depressed people: A crosssituation study. BMC Psychiatry 2019, 19, 1–12, doi:10.1186/s12888-019-2300-7.
    [2019]
  • 96. Darby, J.K.; Hollien, H. Vocal and Speech Patterns of Depressive Patients. Folia Phoniatr. Logop. 1977, 29, 279–291, doi:10.1159/000264098.
    [1977]
  • 95. Nilsonne, Å .; Sundberg, J.; Ternström, S.; Askenfelt, A. Measuring the rate of change of voice fundamental frequency in fluent speech during mental depression. J. Acoust. Soc. Am. 1988, 83, 716–728.
    [1988]
  • 94. Gouyon, F.; Pachet, F.; Delerue, O. On the use of zero-crossing rate for an application of classification of percussive sounds. In Proceedings of the COST G-6 conference on Digital Audio Effects (DAFX-00), Verona, Italy, 7–9 December 2000.
    [2000]
  • 93. Standards Secretariat, A.S.o.A. American National Standard Acoustical Terminology; Acoustical Society of America: Melville, NY, USA, 1994.
    [1994]
  • 91. Schubert, E.; Wolfe, J.; Tarnopolsky, A. Spectral centroid and timbre in complex, multiple instrumental textures. In Proceedings of the international conference on music perception and cognition, North Western University, Evanston, IL, USA, 2004.
    [2004]
  • 90. Chollet, F. Keras: The python deep learning library. Astrophys. Source Code Libr. 2018, ascl-1806.022.
    [2018]
  • 89. Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; et al. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 2011, 12, 2825–2830.
    [2011]
  • 88. Rumelhart, D.E.; Hinton, G.E.; Williams, R.J. Learning Internal Representations by Error Propagation; California Univ San Diego La Jolla Inst for Cognitive Science: San Diego, CA, USA, 1985.
    [1985]
  • 87. Vapnik, V.; Golowich, S.E.; Smola, A.J. Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. In Advances in Neural Information Processing Systems 9; Mozer, M.C., Jordan, M.I., Petsche, T., Eds.; MIT Press: Boston, MA, USA, 1997; pp. 281–287.
    [1997]
  • 85. Bachu, R.G.; Kopparthi, S.; Adapa, B.; Barkana, B.D. Separation of voiced and unvoiced using zero crossing rate and energy of the speech signal. In American Society for Engineering Education (ASEE) Zone Conference Proceedings; 2008.
    [2008]
  • 84. Snell, R.; Milinazzo, F. Formant location from LPC analysis data. IEEE Trans. Speech Audio Process. 1993, 1, 129–134, doi:10.1109/89.222882.
    [1993]
  • 83. McFee, B.; Raffel, C.; Liang, D.; Ellis, D.P.; McVicar, M.; Battenberg, E.; Nieto, O. librosa: Audio and Music Signal Analysis in Python. In Proceedings of the 14th python in science conference 2015, Austin, TX, USA, 6–12 July 2015; pp. 18–24, doi:10.25080/majora-7b98e3ed-003.
  • 82. Belalcázar-Bolaños, E.A.; Orozco-Arroyave, J.R.; Vargas- Bonilla, J.F.; Haderlein, T.; Nöth, E. Glottal Flow Patterns Analyses for Parkinson’s Disease Detection: Acoustic and Nonlinear Approaches. In Proceedings of the Transactions on Petri Nets and Other Models of Concurrency XV; Springer: London New York 2016; pp. 400–407.
  • 81. Moore, E., 2nd; Clements, M.A.; Peifer, J.W.; Weisser, L. Critical analysis of the impact of glottal features in the classification of clinical depression in speech. IEEE Trans. Biomed. Eng. 2008, 55, 96–107.
    [2008]
  • 80. Lee, S.-R.; Lee, W.-H.; Park, J.-S.; Kim, S.-M.; Kim, J.-W.; Shim, J.-H. The Study on Reliability and Validity of Korean Version of the Barratt Impulsiveness Scale-11-Revised in Nonclinical Adult Subjects. J. Korean Neuropsychiatr. Assoc. 2012, 51, 378–386, doi:10.4306/jknpa.2012.51.6.378.
    [2012]
  • 8. Greenberg PE, Fournier AA, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010). J Clin Psychiatry. 2015;76(2):155–62.
  • 79. Spinella, M. Normative data and a short form of the barratt impulsiveness scale. Int. J. Neurosci. 2007, 117, 359–368, doi:10.1080/00207450600588881.
    [2007]
  • 78. Barratt, E.S. Anxiety and impulsiveness related to psychomotor efficiency. Percept. Mot. Ski. 1959, 9, 191–198.
    [1959]
  • 73. Hirschtritt, M.E.; Kroenke, K. Screening for Depression. JAMA 2017, 318, 745–746, doi:10.1001/jama.2017.9820.
    [2017]
  • 71. Zimmerman, M.; Martinez, J.H.; Young, D.; Chelminski, I.; Dalrymple, K. Severity classification on the Hamilton depression rating scale. J. Affect. Disord. 2013, 150, 384–388, doi:10.1016/j.jad.2013.04.028.
    [2013]
  • 70. Bobo, W.V.; Angleró, G.C.; Jenkins, G.; Hall‐Flavin, D.K.; Weinshilboum, R.; Biernacka, J.M. Validation of the 17-item Hamilton Depression Rating Scale definition of response for adults with major depressive disorder using equipercentile linking to Clinical Global Impression scale ratings: Analysis of Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) data. Hum. Psychopharmacol. 2016, 31, 185–192.
  • 7. Sobocki P, Lekander I, Borgstrom F, Strom O, Runeson B. The economic burden of depression in Sweden from 1997 to 2005. Eur Psychiatry. 2007; 22(3):146–52.
    [2007]
  • 69. Hamilton, M. Development of a Rating Scale for Primary Depressive Illness. Br. J. Soc. Clin. Psychol. 1967, 6, 278–296, doi:10.1111/j.2044-8260.1967.tb00530.x.
    [1967]
  • 68. Yoo, S.W.; Kim, Y.S.; Noh, J.S.; Oh, K.S.; Kim, C.H.; NamKoong, K.; Chae, J.H.; Lee, G.C.; Jeon, S.I.; Min, K.J.; et al. Validity of Korean version of the mini-international neuropsychiatric interview. Anxiety Mood 2006, 2, 50–55.
  • 67. Sheehan, D.V.; Lecrubier, Y.; Sheehan, K.H.; Amorim, P.; Janavs, J.; Weiller, E.; Hergueta, T.; Baker, R.; Dunbar, G.C. The Mini- International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 1998, 59.
  • 66. Leucht, S.; Samara, M.; Heres, S.; Patel, M.X.; Furukawa, T.; Cipriani, A.; Geddes, J.; Davis, J.M. Dose Equivalents for Second- Generation Antipsychotic Drugs: The Classical Mean Dose Method. Schizophr. Bull. 2015, 41, 1397–1402, doi:10.1093/schbul/sbv037.
    [2015]
  • 65. Tiihonen, J.; Mittendorfer-Rutz, E.; Torniainen, M.; Alexanderson, K.; Tanskanen, A. Mortality and Cumulative Exposure to Antipsychotics, Antidepressants, and Benzodiazepines in Patients with Schizophrenia: An Observational Follow-Up Study. Am. J. Psychiatry 2016, 173, 600–606, doi:10.1176/appi.ajp.2015.15050618.
    [2016]
  • 64. Isometsa ET. Psychological autopsy studies: a review. Eur Psychiatry 2001;16:379–385.
    [2001]
  • 62. Morales, M. R., & Levitan, R. (2016, December). Speech vs. text: A comparative analysis of features for depression detection systems. In 2016 IEEE spoken language technology workshop (SLT) (pp. 136-143). IEEE.
    [2016]
  • 60. Rodríguez, M.R.; Nuevo, R.; Chatterji, S.; Ayuso-Mateos, J.L. Definitions and factors associated with subthreshold depressive conditions: A systematic review. BMC Psychiatry 2012, 12, 181, doi:10.1186/1471-244x-12-181.
    [2012]
  • 6. Kleine-Budde K, Muller R, Kawohl W, Bramesfeld A, Moock J, Rossler W. The cost of depression - a cost analysis from a large database. J Affect Disord. 2013;147(1–3):137–43.
    [2013]
  • 59. Cuijpers, P.; Smit, F. Subthreshold depression as a risk indicator for major depressive disorder: A systematic review of prospective studies. Acta Psychiatr. Scand. 2004, 109, 325–331.
    [2004]
  • 58. Hall, R.C.; Wise, M.G. The Clinical and Financial Burden of Mood Disorders. Psychosomatics 1995, 36, S11–S18, doi:10.1016/s0033-3182(95)71699-1.
  • 57. Davidson, J.R.; Meltzer-Brody, S. The underrecognition and undertreatment of depression: What is the breadth and depth of the problem? J. Clin. Psychiatry 1999, 60, 4–11.
    [1999]
  • 56. Wagner, H.R.; Burns, B.J.; Broadhead, W.E.; Yarnall, K.S.H.; Sigmon, A.; Gaynes, B. Minor depression in family practice: Functional morbidity, co-morbidity, service utilization and outcomes. Psychol. Med. 2000, 30, 1377–1390, doi:10.1017/s0033291799002998.
    [2000]
  • 55. Wells, K.B.; Burnam, M.A.; Rogers, W.; Hays, R.; Camp, P. The course of depression in adult outpatients: Results from the Medical Outcomes Study. Arch. Gen. Psychiatry 1992, 49, 788– 794.
    [1992]
  • 52. Bright, T. J., Wong, A., Dhurjati, R., Bristow, E., Bastian, L., Coeytaux, R. R., ... & Lobach, D. (2012). Effect of clinical decision-support systems: a systematic review. Annals of internal medicine, 157(1), 29-43.
    [2012]
  • 5. Wagner CJ, Metzger FG, Sievers C, Marschall U, L'Hoest H, Stollenwerk B, et al. Depression-related treatment and costs in Germany: do they change with comorbidity? A claims data analysis. J Affect Disord. 2016;193:257–66.
    [2016]
  • 49. Yang, L., Sahli, H., Xia, X., Pei, E., Oveneke, M. C., & Jiang, D. (2017, October). Hybrid depression classification and estimation from audio video and text information. In Proceedings of the 7th annual workshop on audio/visual emotion challenge (pp. 45-51).
    [2017]
  • 48. Guntuku, S. C., Yaden, D. B., Kern, M. L., Ungar, L. H., & Eichstaedt, J. C. (2017). Detecting depression and mental illness on social media: an integrative review. Current Opinion in Behavioral Sciences, 18, 43-49.
    [2017]
  • 47. Al Asad, N., Pranto, M. A. M., Afreen, S., & Islam, M. M. (2019, November). Depression detection by analyzing social media posts of user. In 2019 IEEE International Conference on Signal Processing, Information, Communication & Systems (SPICSCON) (pp. 13-17). IEEE.
    [2019]
  • 46. Parrott, S., et al., Social Media and Suicide: A Validation of Terms to Help Identify Suicide-related Social Media Posts. J Evid Based Soc Work (2019), 2020. 17(5): p. 624-634.
  • 45. Sawhney, R., et al., Robust suicide risk assessment on social media via deep adversarial learning. J Am Med Inform Assoc, 2021. 28(7): p. 1497-1506.
  • 40. Sourirajan, V., et al., A machine learning approach to detect suicidal ideation in us veterans based on acoustic and linguistic features of speech. arXiv preprint arXiv:2009.09069, 2020.
    [2020]
  • 4. TB USTUN. Global burden of depressive disorders in the year 2000. British J Psychiatry. 2004;184:3 8 6–9 2.
    [2004]
  • 39. Hashim, N.W., Wilkes, M., Salomon, R., Meggs, J., 2012. Analysis of timing pattern of speech as possible indicator for near-term suicidal risk and depression in male patients. In: 2012 International Conference on Signal Processing Systems (ICSPS 2012), pp. 6–13.
    [2012]
  • 38. Zhao, Y., et al., Multi-Head Attention-Based Long Short-Term Memory for Depression Detection From Speech. Front Neurorobot, 2021. 15: p. 684037.
  • 37. Vazquez-Romero, A. and A. Gallardo-Antolin, Automatic Detection of Depression in Speech Using Ensemble Convolutional Neural Networks. Entropy (Basel), 2020. 22(6).
    [2020]
  • 35. Little, B., et al., Deep learning-based automated speech detection as a marker of social functioning in late-life depression. Psychol Med, 2021. 51(9): p. 1441-1450.
  • 34. Cummins, N., et al., A review of depression and suicide risk assessment using speech analysis. Speech Communication, 2015. 71: p. 10-49.
    [2015]
  • 33. A. Ozdas, R.G. Shiavi, S.E. Silverman, M.K. Silverman, D.M. Wilkes, Investigation of vocal jitter and glottal flow spectrum as possible cues for depression and near-term suicidal risk, IEEE Trans. Bio-Eng., 51 (2004), pp. 1530-1540
    [2004]
  • 30. E. Kraepelin, Manic depressive insanity and paranoia. J. Nerv. Ment. Dis., 53 (1921), p. 350
  • 3. Mathers, C.D. and D. Loncar, Updated projections of global mortality and burden of disease, 2002-2030: data sources, methods and results. Geneva: World Health Organization, 2005.
    [2005]
  • 25. Ghasemi, P., A. Shaghaghi, and H. Allahverdipour, Measurement Scales of Suicidal Ideation and Attitudes: A Systematic Review Article. Health Promot Perspect, 2015. 5(3): p. 156-68.
    [2015]
  • 21. Sheehan, D.V., Depression: underdiagnosed, undertreated, underappreciated. Manag Care, 2004. 13(6 Suppl Depression): p. 6-8.
    [2004]
  • 19. Kawakamia N, Shimizub H, Haratanic T, Iwatad N. Kitamurae T. lifetime and 6-month prevalence of DSM-III-R psychiatric disorders in an urban community in Japan. Psychiatry Res. 2004;121:293–301.
    [2004]
  • 18. Kessler RC, Chiu WT, Demler O, Walters EE. Prevalence, severity, and Comorbidityof 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:617–709.
    [2005]
  • 17. International Statistical Classification of Diseases and Related Health Problems. Tenth Revision. Vol. 1. 1992, Geneva: World Health Organization.
    [1992]
  • 164. Stawarz, K., Preist, C., Tallon, D., Thomas, L., Turner, K., Wiles, N., ... & Coyle, D. (2020, April). Integrating the Digital and the Traditional to Deliver Therapy for Depression: Lessons from a Pragmatic Study. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-14).
  • 163. Lee, J. M., Cho, B. H., Ku, J. H., Kim, J. S., Lee, J. H., Kim, I. Y., & Kim, S. I. (2001, October). A study on the system for treatment of ADHD using virtual reality. In 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Vol. 4, pp. 3754-3757). IEEE.
  • 161. Jansson, L., & Nordgaard, J. (2016). The psychiatric interview for differential diagnosis (Vol. 270). Switzerland: springer.
    [2016]
  • 16. Association, A.P., Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). 2013, Arlington, VA, US.: American Psychiatric Pub.
    [2013]
  • 158. Gyllensten, A. L., Öberg, H., Träskman-Bendz, L., & Ekdahl, C. (1997). Psychomotor functioning in suicide attempters: An explorative study using the Resource Oriented Body Examination of Bunkan. Nordic Journal of Psychiatry, 51(3), 193-200.
    [1997]
  • 156. France, D. J., Shiavi, R. G., Silverman, S., Silverman, M., & Wilkes, M. (2000). Acoustical properties of speech as indicators of depression and suicidal risk. IEEE transactions on Biomedical Engineering, 47(7), 829-837.
    [2000]
  • 155. Hönig, F., Batliner, A., Nöth, E., Schnieder, S., & Krajewski, J. (2014). Automatic modelling of depressed speech: relevant features and relevance of gender.
    [2014]
  • 153. Nilsonne, Å., Sundberg, J., Ternström, S., & Askenfelt, A. (1988). Measuring the rate of change of voice fundamental frequency in fluent speech during mental depression. The Journal of the Acoustical Society of America, 83(2), 716-728.
    [1988]
  • 152. Ozdas, A., Shiavi, R. G., Silverman, S. E., Silverman, M. K., & Wilkes, D. M. (2004). Investigation of vocal jitter and glottal flow spectrum as possible cues for depression and near-term suicidal risk. Ieee transactions on Biomedical engineering, 51(9), 1530- 1540.
    [2004]
  • 150. Croarkin, P. E., Levinson, A. J., & Daskalakis, Z. J. (2011). Evidence for GABAergic inhibitory deficits in major depressive disorder. Neuroscience & Biobehavioral Reviews, 35(3), 818- 825.
    [2011]
  • 15. Palmer, C. S., Halpern, M. T., & Hatziandreu, E. J. (1995). The cost of suicide and suicide attempts in the United States. Clinical Neuropharmacology, 18, S25-S33.
    [1995]
  • 148. Nicolai, J., Darancó, S., & Moshagen, M. (2016). Effects of mood state on impulsivity in pathological buying. Psychiatry Research, 244, 351-356.
    [2016]
  • 147. Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of clinical psychology, 51(6), 768-774.
    [1995]
  • 145. Carli, V., Jovanović, N., Podlešek, A., Roy, A., Rihmer, Z., Maggi, S., ... & Sarchiapone, M. (2010). The role of impulsivity in self-mutilators, suicide ideators and suicide attempters—A study of 1265 male incarcerated individuals. Journal of affective disorders, 123(1-3), 116-122.
  • 144. Taylor, J., Kemper, T. S., Loney, B. R., & Kistner, J. A. (2006). Classification of severe male juvenile offenders using the MACI clinical and personality scales. Journal of Clinical Child and Adolescent Psychology, 35(1), 90-102.
    [2006]
  • 143. Sanislow, C. A., Grilo, C. M., Fehon, D. C., Axelrod, S. R., & McGlashan, T. H. (2003). Correlates of suicide risk in juvenile detainees and adolescent inpatients. Journal of the American Academy of Child & Adolescent Psychiatry, 42(2), 234-240.
    [2003]
  • 142. Davidson, C. L., Wingate, L. R., Grant, D. M., Judah, M. R., & Mills, A. C. (2011). Interpersonal suicide risk and ideation: The influence of depression and social anxiety. Journal of Social and Clinical Psychology, 30(8), 842-855.
    [2011]
  • 141. Davidson, C. L., Wingate, L. R., Grant, D. M., Judah, M. R., & Mills, A. C. (2011). Interpersonal suicide risk and ideation: The influence of depression and social anxiety. Journal of Social and Clinical Psychology, 30(8), 842-855.
    [2011]
  • 140. Johnson, J., Weissman, M. M., & Klerman, G. L. (1990). Panic disorder, comorbidity, and suicide attempts. Archives of General Psychiatry, 47(9), 805-808.
    [1990]
  • 14. Statistics Korea. Causes of Death Statistics in 2018 [Internet]. 2019 [cited 13 October 2019]. [Available from: http://kosis.kr/statisticsList/statisticsListIndex.do?menuId=M_0 1_01&vwcd=MT_ZTITLE&parmTabId=M_01_01
  • 139. Mannuzza, S., Aronowitz, B., Chapman, T., Klein, D. F., & Fyer, A. J. (1992). Panic disorder and suicide attempts. Journal of Anxiety Disorders, 6(3), 261-274.
    [1992]
  • 137. Blazer, D. G., Hughes, D. C., & George, L. K. (1992). Age and impaired subjective support: Predictors of depressive symptoms at one-year follow-up. Journal of Nervous and Mental Disease.
    [1992]
  • 136. Naushad, N., Dunn, L. B., Muñoz, R. F., & Leykin, Y. (2018). Depression increases subjective stigma of chronic pain. Journal of affective disorders, 229, 456-462.
    [2018]
  • 132. Lim, A. Y., Lee, A. R., Hatim, A., Tian-Mei, S., Liu, C. Y., Jeon, H. J., ... & Hong, J. P. (2014). Clinical and sociodemographic correlates of suicidality in patients with major depressive disorder from six Asian countries. BMC psychiatry, 14(1), 1-8.
    [2014]
  • 130. Cochrane-Brink, K. A., Lofchy, J. S., & Sakinofsky, I. (2000). Clinical rating scales in suicide risk assessment. General Hospital Psychiatry, 22(6), 445-451.
    [2000]
  • 13. Naghavi, M. and C. Global Burden of Disease Self-Harm, Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the Global Burden of Disease Study 2016. BMJ, 2019. 364: p. l94.
    [2019]
  • 129. General, S. (2012). National Strategy for Suicide Prevention: Goals and Objectives for Action. US Department of Health and Human Services Office of the Surgeon General and National Action Alliance for Suicide Prevention; 2012.[Accessed: July 29, 2015].
  • 126. Alghowinem, S., Goecke, R., Wagner, M., Epps, J., Gedeon, T., Breakspear, M., & Parker, G. (2013, May). A comparative study of different classifiers for detecting depression from spontaneous speech. In 2013 IEEE international conference on acoustics, speech and signal processing (pp. 8022-8026). IEEE.
    [2013]
  • 125. Cummins, N., Epps, J., Breakspear, M., & Goecke, R. (2011). An investigation of depressed speech detection: Features and normalization. In Twelfth Annual Conference of the International Speech Communication Association.
    [2011]
  • 124. Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., ... & Dunbar, G. C. (1998). The Mini- International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of clinical psychiatry, 59(20), 22-33.
  • 123. Esposito, A., Esposito, A. M., Likforman-Sulem, L., Maldonato, M. N., & Vinciarelli, A. (2016). On the significance of speech pauses in depressive disorders: results on read and spontaneous narratives. In Recent advances in nonlinear speech processing (pp. 73-82). Springer, Cham.
    [2016]
  • 122. Fant, G. (1962). Formant bandwidth data. STL-QPSR, 3, 1- 2.
    [1962]
  • 121. DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988). Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, 837-845.
    [1988]
  • 120. Bird, S., E. Klein, and E. Loper, Natural language processing with Python: analyzing text with the natural language toolkit. 2009: " O'Reilly Media, Inc."
    [2009]
  • 12. World Health Organization. Mental health: Suicide data [Internet]. 2019 [cited 13 October 2019]. [Available from: https://www.who.int/mental_health/prevention/suicide/suicidepre vent/en/
    [2019]
  • 118. Öztuna, D., A.H. Elhan, and E. Tüccar, Investigation of four different normality tests in terms of type 1 error rate and power under different distributions. Turkish Journal of Medical Sciences, 2006. 36(3): p. 171-176.
    [2006]
  • 113. "Linear & Quadratic Discriminant Analysis · UC Business Analytics R Programming Guide". uc-r.github.io. Retrieved 2020-03-29.
  • 112. Oon-Arom, A., Wongpakaran, T., Kuntawong, P., & Wongpakaran, N. (2021). Attachment anxiety, depression, and perceived social support: a moderated mediation model of suicide ideation among the elderly. International psychogeriatrics, 33(2), 169-178.
  • 111. Jiang, L., Cao, Y., Ni, S., Chen, X., Shen, M., Lv, H., & Hu, J. (2020). Association of sedentary behavior with anxiety, depression, and suicide ideation in college students. Frontiers in psychiatry, 11, 1403.
    [2020]
  • 110. West, S.G., J.F. Finch, and P.J. Curran, Structural equation models with nonnormal variables: Problems and remedies. 1995.
    [1995]
  • 108. Lai, K., et al., Assessing Suicide Reporting in Top Newspaper Social Media Accounts in China: Content Analysis Study. JMIR Ment Health, 2021. 8(5): p. e26654.
  • 106. Van Hee, C.; Lefever, E.; Hoste, V. SemEval-2018 Task 3: Irony Detection in English Tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation, New Orleans, LA, USA, 5–6 June 2018; Association for Computational Linguistics: 2018; pp. 39–50.
    [2018]
  • 105. Nakov, P.; Ritter, A.; Rosenthal, S.; Sebastiani, F.; Stoyanov, V. SemEval-2016 Task 4: Sentiment Analysis in Twitter. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016); Association for Computational Linguistics (ACL): 2016; pp. 1–18.
    [2016]
  • 104. Judd, L.L.; Akiskal, H.S.; Maser, J.D.; Zeller, P.J.; Endicott, J.; Coryell, W.; Paulus, M.; Kunovac, J.L.; Leon, A.C.; I Mueller, T.; et al. Major depressive disorder: A prospective study of residual subthreshold depressive symptoms as predictor of rapid relapse. J. Affect. Disord. 1998, 50, 97–108, doi:10.1016/s0165- 0327(98)00138-4.
  • 103. Meeks, T.W.; Vahia, I,V.; Lavretsky, H.; Kulkarni, G.; Jeste, D.V. A tune in “a minor” can “b major”: A review of epidemiology, illness course, and public health implications of subthreshold depression in older adults. J. Affect. Disord. 2011, 129, 126–142.
  • 102. Cannizzaro, M.; Harel, B.; Reilly, N.; Chappell, P.; Snyder, P.J. Voice acoustical measurement of the severity of major depression. Brain Cogn. 2004, 56, 30–35, doi:10.1016/j.bandc.2004.05.003.
    [2004]
  • 101. Mundt, J.C.; Snyder, P.; Cannizzaro, M.S.; Chappie, K.; Geralts, D.S. Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology. J. Neurolinguistics 2007, 20, 50–64, doi:10.1016/j.jneuroling.2006.04.001.
    [2007]
  • 100. Darby, J.K.; Hollien, H. Vocal and Speech Patterns of Depressive Patients. Folia Phoniatr. Logop. 1977, 29, 279–291, doi:10.1159/000264098.
    [1977]
  • 10. Shin, D., Kim, N. W., Kim, M. J., Rhee, S. J., Park, C. H. K., Kim, H., ... & Ahn, Y. M. (2020). Cost analysis of depression using the national insurance system in South Korea: a comparison of depression and treatment-resistant depression. BMC health services research, 20(1), 1-11.