مقاله انگلیسی رایگان در مورد به اشتراک گذاری منابع داده بزرگ پزشکی – IEEE 2019

IEEE

 

مشخصات مقاله
ترجمه عنوان مقاله تجزیه و تحلیل و اجرای مصورسازی مکانیسم به اشتراک گذاری منابع داده بزرگ پزشکی بر اساس یادگیری عمیق
عنوان انگلیسی مقاله Analysis and Visualization Implementation of Medical Big Data Resource Sharing Mechanism Based on Deep Learning
انتشار مقاله سال ۲۰۱۹
تعداد صفحات مقاله انگلیسی ۱۲ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۴٫۶۴۱ در سال ۲۰۱۸
شاخص H_index ۵۶ در سال ۲۰۱۹
شاخص SJR ۰٫۶۰۹ در سال ۲۰۱۸
شناسه ISSN ۲۱۶۹-۳۵۳۶
شاخص Quartile (چارک) Q2 در سال ۲۰۱۸
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر، مدیریت
گرایش های مرتبط هوش مصنوعی، مدیریت منابع اطلاعاتی
نوع ارائه مقاله
ژورنال
مجله / کنفرانس دسترسی – IEEE Access
دانشگاه  School of Management, Xinxiang Medical University, Xinxiang 453003, China
کلمات کلیدی داده بزرگ پزشکی، مصورسازی داده، مکانیسم به اشتراک گذاری منابع اطلاعاتی، یادگیری عمیق
کلمات کلیدی انگلیسی  Medical big data, data visualization, information resource sharing mechanism, deep learning
شناسه دیجیتال – doi
https://doi.org/10.1109/ACCESS.2019.2949879
کد محصول  E13911
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
I. Introduction
II. Related Theories and Methods
III. Parallel Optimization of Deep Learning Algorithms for Medical Big Data Processing
IV. Analysis of Regional Information Resource Sharing Mechanism Based on Medical Big Data
V. Medical Big Data Visualization Implementation
Authors
Figures
References

 

بخشی از متن مقاله:
Abstract

With the development of information technology, the informationization of the medical industry is also constantly developing rapidly, and medical data is growing exponentially. In the context of ‘‘Big Data +’’, people began to study the application of data visualization to medical data. Data visualization can make full use of the human sensory vision system to guide users through data analysis and present information hidden behind the data in an intuitive and easy-to-use manner. This paper first introduces the workflow of DBN, a deep learning algorithm, and summarizes the computational characteristics of the algorithm. The classification function is translated into an assembler using an instruction set-based assembly language, and the program is evaluated for performance. Secondly, based on the Hadoop ecosystem, this paper analyzes the BDMISS system for big data medical information resource sharing. Based on the system’s requirements and functional positioning, from the medical information collection and sharing, data mining and knowledge management level, the big data medical service system is constructed. Based on the semantic network and ontology theory, big data mining technology and the design of ‘‘medical cloud’’, the resource sharing mechanism is analyzed. Based on the Spring MVC framework, using Echarts, HCharts and other data visualization technology, according to the design of specific modules, the visualization and display of medical data is realized, which has certain promotion effect on the research and development of medical big data visualization analysis.

Introduction

As the informationization of the medical industry continues to develop rapidly, medical data has grown exponentially, and medical big data has brought tremendous pressure on existing hospital information systems. With the emergence of various unstructured data, traditional medical information systems cannot meet the requirements of big data in terms of storage space, storage speed, storage structure, etc., some data is lost, resulting in loss of valuable medical data [1]–[۳]. The data integrity of the system is not enough, and the data processing speed is slow, which cannot meet the user’s demand for data visualization display [4]. In recent years, the information and communication industry of medical and health has ushered in the opportunity of development. The hospital information management system, public health service platform, telemedicine, mobile medical, and information equipment have formed a scale of 100 billion yuan. Medical informatization is no longer limited to transactional tasks such as hospital information management systems [5], [6]. Applications and research based onInternet of Things and cloud computing continue to deepen, and medical informatization begins to develop in the areas of process optimization and service innovation [7]. The Internet of Things and cloud computing have changed the patterns and paths of medical information services, optimized medical service processes, improved the efficiency of medical services, and transformed medical information sharing and service models [8], [9]. Deep learning not only improves people’s lives in traditional industries, but as people’s attention to physical health increases, machine learning algorithms closely related to deep learning have emerged in the health care field.

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