دانلود مقاله انگلیسی رایگان:استفاده از یادگیری ماشین برای توضیح ناهمگونی اسکیزوفرنی: تحقق وعده و پرهیز از اعتیاد به مواد مخدر - 2019
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  • Using machine learning to explain the heterogeneity of schizophrenia: Realizing the promise and avoiding the hype Using machine learning to explain the heterogeneity of schizophrenia: Realizing the promise and avoiding the hype
    Using machine learning to explain the heterogeneity of schizophrenia: Realizing the promise and avoiding the hype

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    Using machine learning to explain the heterogeneity of schizophrenia: Realizing the promise and avoiding the hype


    ترجمه فارسی عنوان مقاله:

    استفاده از یادگیری ماشین برای توضیح ناهمگونی اسکیزوفرنی: تحقق وعده و پرهیز از اعتیاد به مواد مخدر


    منبع:

    Sciencedirect - Elsevier - Schizophrenia Research, Corrected proof: doi:10:1016/j:schres:2019:08:032


    نویسنده:

    Neeraj Tandon, Rajiv Tandon ⁎


    چکیده انگلیسی:

    Despite extensive research and prodigious advances in neuroscience, our comprehension of the nature of schizophrenia remains rudimentary.Our failure to make progress is attributed to the extremeheterogeneity of this condition, enormous complexity of the human brain, limitations of extant research paradigms, and inadequacy of traditional statistical methods to integrate or interpret increasingly large amounts of multidimensional information relevant to unravelling brain function. Fortunately, the rapidly developing science of machine learning appears to provide tools capable of addressing each of these impediments. Enthusiasm about the potential of machine learning methods to break the current impasse is reflected in the steep increase in the number of scientific publication about the application of machine learning to the study of schizophrenia. Machine learning approaches are, however, poorly understood by schizophrenia researchers and clinicians alike. In this paper, we provide a simple description of the nature and techniques of machine learning and their application to the study of schizophrenia.We then summarize its potential and constraints with illustrations fromsix studies of machine learning in schizophrenia and address some common misconceptions about machine learning.Wesuggest some guidelines for researchers, readers, science editors and reviewers of the burgeoning machine learning literature in schizophrenia. In order to realize its enormous promise,we suggest the need for the disciplined application of machine learning methods to the study of schizophrenia with a clear recognition of its capability and challenges accompanied by a concurrent effort to improve machine learning literacy among neuroscientists and mental health professionals.
    Keywords: Machine learning | Schizophrenia | Methods | Research | Neuroscience | Computational psychiatry | -omics | Big data | Hype | Promise


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 6
    حجم فایل: 293 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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