دانلود مقاله انگلیسی رایگان:شناسایی عوامل موثر در تشخیص تکرار مجدد در بین بیماران مجرم با تشخیص اسکیزوفرنی از طریق الگوریتم های یادگیری ماشین - 2020
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  • Identifying influential factors distinguishing recidivists among offender patients with a diagnosis of schizophrenia via machine learning algorithms Identifying influential factors distinguishing recidivists among offender patients with a diagnosis of schizophrenia via machine learning algorithms
    Identifying influential factors distinguishing recidivists among offender patients with a diagnosis of schizophrenia via machine learning algorithms

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Identifying influential factors distinguishing recidivists among offender patients with a diagnosis of schizophrenia via machine learning algorithms


    ترجمه فارسی عنوان مقاله:

    شناسایی عوامل موثر در تشخیص تکرار مجدد در بین بیماران مجرم با تشخیص اسکیزوفرنی از طریق الگوریتم های یادگیری ماشین


    منبع:

    Sciencedirect - Elsevier - Forensic Science International, 315 (2020) 110435. doi:10.1016/j.forsciint.2020.110435


    نویسنده:

    Johannes Kirchebnerb,1, Moritz Philipp Günthera,1,*, Steffen Laub


    چکیده انگلیسی:

    Purpose: There is a lack of research on predictors of criminal recidivism of offender patients diagnosed with schizophrenia. Methods: 653 potential predictor variables were anlyzed in a set of 344 offender patients with a diagnosis of schizophrenia (209 reconvicted) using machine learning algorithms. As a novel methodological approach, null hypothesis significance testing (NHST), backward selection, logistic regression, trees, support vector machines (SVM), and naive bayes were used for preselecting variables. Subsequently the variables identified as most influential were used for machine learning algorithm building and evaluation. Results: The two final models (with/without imputation) predicted criminal recidivism with an accuracy of 81.7 % and 70.6 % and a predictive power (area under the curve, AUC) of 0.89 and 0.76 based on the following predictors: prescription of amisulpride prior to reoffending, suspended sentencing to imprisonment, legal complaints filed by relatives/therapists/public authorities, recent legal issues, number of offences leading to forensic treatment, anxiety upon discharge, being single, violence toward care team and constant breaking of rules during treatment, illegal opioid use, middle east as place of birth, and time span since the last psychiatric inpatient treatment. Conclusion: Results provide new insight on possible factors influencing persistent offending in a specific subgroup of patients with a schizophrenic spectrum disorder.
    Keywords: Criminal justice | Criminal recidivism | Machine learning | Offender | Schizophrenia


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 7
    حجم فایل: 266 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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