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Schizophrenia Auxiliary Diagnosis System Based on Data Mining Technology

  • Image & Signal Processing
  • Published:
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Abstract

In order to use digital medical technology to develop and design an auxiliary diagnosis system for schizophrenia to assist doctors at all levels to diagnose and predict the cure of patients, improve the accuracy of diagnosis of symptoms, find complications in advance, and reduce the risk of disease, the application of Bayesian network in auxiliary diagnosis system of schizophrenia is studied, and an auxiliary diagnosis system of schizophrenia is designed. Based on data mining technology, knowledge information can be found from patient data and used to diagnose the nature of patients. The demand analysis of auxiliary diagnosis system is briefly introduced, and an auxiliary diagnosis system for schizophrenia based on Bayesian network is designed.

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References

  1. Sacchi, S., Pieragnoli, P., and Ricciardi, G., Impact of haemodynamic SonR sensor on monitoring of left ventricular function in patients undergoing cardiac resynchronization therapy. EP Europace 19(10):1695–1699, 2016.

    Article  Google Scholar 

  2. Quintero, D. G., Taylor, R. B., and Miller, M. B., Air-abrasive disinfection of implant surfaces in a simulated model of periimplantitis. Implant Dentistry 26(3):423, 2017.

    Article  Google Scholar 

  3. Wang, X., Lian, Y., and Wang, X., Study of regional left ventricular longitudinal function in fetuses with gestational diabetes mellitus by velocity vector imaging. Echocardiography 33(8):1228–1233, 2016.

    Article  Google Scholar 

  4. Versiani, M. A., Ordinola-Zapata, R., and Keleş, A., Middle mesial canals in mandibular first molars: A micro-CT study in different populations. Archives of Oral Biology 61:130–137, 2016.

    Article  Google Scholar 

  5. Tardif, R., Catto, C., and Haddad, S., Assessment of air and water contamination by disinfection by-products at 41 indoor swimming pools. Environmental Research 148:411–420, 2016.

    Article  CAS  Google Scholar 

  6. Ojaghi-Haghighi, Z., Mohebbi, B., and Moladoust, H., Left ventricular torsional parameters before and after atrial fibrillation ablation: A velocity vector imaging study. Electronic Physician 9(9):5395–5401, 2017.

    Article  Google Scholar 

  7. Chauveau, S., Anyukhovsky, E. P., and Benari, M., Induced pluripotent stem cell-derived cardiomyocytes provide in vivo biological pacemaker function. Circulation Arrhythmia & Electrophysiology 10(5):e004508, 2017.

    Article  Google Scholar 

  8. Lo, Q., Haluska, B., and Chia, E. M., Alterations in regional myocardial deformation assessed by strain imaging in cardiac amyloidosis. Echocardiography 33(12):1844, 2016.

    Article  Google Scholar 

  9. Shen, Y., Xu, J., Li, Z., Analysis of gut microbiota diversity and auxiliary diagnosis as a biomarker in patients with schizophrenia: A cross-sectional study. Schizophr. Res. 197, 2018.

    Article  Google Scholar 

  10. Ildiz, G. O., Arslan, M., and Unsalan, O., FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases. Spectrochimica Acta Part A Molecular & Biomolecular Spectroscopy 152:551–556, 2016.

    Article  Google Scholar 

  11. Zhang, L. X., Gu, W. J., Li, Y. J., Wang, Y., Wang, W. B., Wang, A. P. et al., PTH is a promising auxiliary index for the clinical diagnosis of aldosterone-producing adenoma. American Journal of Hypertension 29(5):575–581, 2015.

    Article  Google Scholar 

  12. Qi, X. K., Liu, J. G., Li, C. Q., and Ning, B. O., 27 cases of atypical viral encephalitis with obvious psychiatric symptom but negative auxiliary diagnosis. Journal of the Neurological Sciences 357:e115–e116, 2015.

    Article  Google Scholar 

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Funding

There was no dedicated funding regarding this study.

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Authors and Affiliations

  1. Department of Psychiatry, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001, China

    Xiaohong Wang, Na Zhao & Jian Hu

  2. School of Management, Harbin Institute of Technology, Harbin, 150001, China

    Peng Ouyang

  3. Beijing Electro-Mechanical Engineering Institute, Beijing, 100074, China

    Jiayi Lin

Authors
  1. Xiaohong Wang
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  2. Na Zhao
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  3. Peng Ouyang
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  4. Jiayi Lin
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  5. Jian Hu
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Corresponding author

Correspondence to Jian Hu.

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Conflict of Interest

Author Xiaohong Wang declares that he has no conflict of interest. Author Na Zhao declares that he has no conflict of interest. Author Peng Ouyang declares that he has no conflict of interest. Author Jiayi Lin declares that he has no conflict of interest. Author Jian Hu declares that he has no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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This article is part of the Topical Collection on Image & Signal Processing

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Wang, X., Zhao, N., Ouyang, P. et al. Schizophrenia Auxiliary Diagnosis System Based on Data Mining Technology. J Med Syst 43, 125 (2019). https://doi.org/10.1007/s10916-019-1214-8

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  • DOI: https://doi.org/10.1007/s10916-019-1214-8

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