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Caught in the Net: How Digital Media Shapes Mental Illnesses in Youth and How Psychiatrists Should Respond

机译：陷入网：数字媒体如何在青年中造成精神疾病以及精神科医生应该如何应对

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《Journal of the American Academy of Child and Adolescent Psychiatry》 |2018年第10期|共2页
作者
Kristopher Kaliebe;
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作者单位

University of South Florida;

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原文格式 PDF
正文语种 eng
中图分类精神病学;
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1. Caught in the Net: How Digital Media Shapes Mental Illnesses in Youth and How Psychiatrists Should Respond [J] . Kristopher Kaliebe Journal of the American Academy of Child and Adolescent Psychiatry . 2018,第10期

机译：陷入网：数字媒体如何在青年中造成精神疾病以及精神科医生应该如何应对
2. To what extent are psychiatrists aware of the comorbid somatic illnesses of their patients with serious mental illnesses? – a cross-sectional secondary data analysis [J] . Christina Dornquast, Juliane Tomzik, Thomas Reinhold, BMC Health Services Research . 2017,第1期

机译：精神科医生在多大程度上意识到其患有严重精神疾病的患者所患的躯体疾病？ –横断面二级数据分析
3. To what extent are psychiatrists aware of the comorbid somatic illnesses of their patients with serious mental illnesses? – a cross-sectional secondary data analysis [J] . Christina Dornquast, Juliane Tomzik, Thomas Reinhold, BMC Health Services Research . 2017,第1期

机译：精神科医生在多大程度上意识到其患有严重精神疾病的患者所患的躯体疾病？ –横断面二级数据分析
4. Classification of mental illnesses on social media using RoBERTa [C] . Ankit Murarka, Balaji Radhakrishnan, Sushma Ravichandran International Workshop on Health Text Mining and Information Analysis . 2021

机译：利用罗伯塔对社交媒体精神疾病的分类
5. Supports provided by people with mental illnesses in a rehabilitation program in southern Taiwan: An exploratory study using social network analysis (China). [D] . Hsu, Su-Ting. 2005

机译：精神疾病患者在台湾南部的康复计划中提供的支持：一项使用社交网络分析的探索性研究（中国）。
6. To what extent are psychiatrists aware of the comorbid somatic illnesses of their patients with serious mental illnesses? – a cross-sectional secondary data analysis [O] . Christina Dornquast, Juliane Tomzik, Thomas Reinhold, 2017

机译：精神科医生在多大程度上意识到其患有严重精神疾病的患者所患的躯体疾病？ –横断面二级数据分析
7. ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail [O] . Pranav S. Wazarkar 2020

机译：摘要的各个身体部位或器官可被分析以识别在人体内的不同的疾病。指甲分析来识别人体疾病的方法之一。指甲是身体一部分是离心脏最远，因此在最后接受氧气。作为结果，指甲是第一谁表现出人体疾病的症状。指甲可以容易地捕获用于诊断和没有重装或需要使用指甲图像用于疾病诊断，比如在其他测试和扫描过程没有特定的条件。人的指甲提供有关投诉或取决于它们的形状，纹理和色彩在人体内的任何营养失衡有益的信息。在人类中，许多全身性皮肤疾病是可以很容易地通过两个四肢指甲的仔细检查分析。很多指甲病已发现众多潜在系统性疾病的主要症状。在指甲的颜色，质地和形状的变化是许多疾病主要影响指甲的迹象。考虑到所有的指甲的这些性能的系统被提出，用于识别人指甲这样的变化以获得更精确的结果，并毫不费力预测许多疾病用途的数字图像处理（DIP）方法。随着物联网（IOT）的概念，新兴的互联网将生成的报告提供远程，这将帮助用户降低运输工作。由于系统必须处理大量的私人数据，数据的安全性必须得到保证。为了保持数据的机密性，使用Blockchain的概念，它是在数据管理领域的大多数新兴的概念之一。本文包含了数字图像处理的指甲图像，IOT（ThingSpeak云）的使用为数据存储和执行Blockchain的特征提取的执行，以保持固定的系统和盗窃免费。关键词：诠释薄GS（IOT），图像的ERNET PROC essin克，薄型gSpeak，RG乙vavalues，平均数PI XEL vavalues，阵营kchain，哈希密钥。疾病诊断系统：在人类指甲异常
8. Responding to People Who Have Been Victimized by Individuals with Mental Illnesses [R] . Ward, M. A., Glassberg, H. 2008

机译：回应遭受精神疾病的个人受害的人

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