Personalized Psychiatry

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Big Data Analytics in Mental Health

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Big Data Analytics in Mental Health

Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. To fill these gaps, analysis in science, industry, and government seeks to use "big data" for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets - also known as big data - to fulfill their mission. Briefly, big data is characterized by high volume, high velocity and variety of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new statistical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century. This book will benefit clinicians, practitioners and scientists in the field of psychiatry, psychology and behavioral sciences and ultimately patients with mental illness. Authors also intend to reach postgraduate students and undergraduate students in these fields. The main aims are 1) to empower researchers with a different way to conceptualize studies in psychiatry by using big data analytics approach; 2) to give clinicians a broad perspective about how clinical decisions such as selection of treatment options, preventive strategies, and prognosis orientations can be changed by a big data approach; 3) to provide a unique opportunity to showcase innovative solutions tackling complex problems in mental health using big data and machine learning; 4) to discuss challenges in terms of what data could be used without jeopardizing individual privacy and freedom.
The table of contents is broad and comprehensive, discussing the topic in a very didactical way. It starts with introductory chapters about big-data analytics and related topics, then following with specific topics discussing the applicability of these statistical methods to psychiatry. It ends with chapters highlighting the next steps in this field and discussing ethical issues related to big-data research in mental health.
For a detailed description of each chapter, please check the file "Core Information," under the "Attachments" tab. The Volume Editors are internationally renowned either in psychiatric research or big-data analytics. Highlights to Dr. Flavio Kapczinski, a Brazilian psychiatrist who recently moved to MacMaster Univesity and was recently listed by Clarivate Analytics among the most influential psychiatrists.

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گزارش تخلف

مغایرت عنوان کتاب با توضیحات و تصویر جلد
عدم رعایت حقوق نشر طبق قوانین جمهوری اسلامی ایران
محتوای مستهجن
توهین به قومیتها و محتوای نژادپرستی
توهین به اقیلیتهای مذهبی
اهانت به مقامات سیاسی و مذهبی
اشاعه ی کودک آزاری
سایر موارد

بستن

فرمت کتاب

ebook

زبان

english

تاریخ انتشار

2019

نویسنده

Flavio Kapczinski

ناشر

Springer

شابک

9783030035525

20,000 تومان

خرید کتاب مطالعه نمونه درخواست ترجمه کتاب

خرید کتاب Personalized Psychiatry

Personalized Psychiatry

گزارش تخلف

فرمت کتاب

ebook

زبان

english

تاریخ انتشار

2019

نویسنده

ناشر

شابک

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