The Challenges of Diagnostic Imaging in the Era of Big Data

Author:

Aiello MarcoORCID,Cavaliere Carlo,D’Albore Antonio,Salvatore Marco

Abstract

The diagnostic imaging field has undergone considerable growth both in terms of technological development and market expansion; with the following increasing production of a considerable amount of data that potentially fully poses diagnostic imaging in the Big data in the context of healthcare. Nevertheless, the mere production of a large amount of data does not automatically permit the real exploitation of their intrinsic value. Therefore, it is necessary to develop digital platforms and applications that favor the correct and advantageous management of diagnostic images such as Big data. This work aims to frame the role of diagnostic imaging in this new scenario, emphasizing the open challenges in exploiting such intense data generation for decision making with Big data analytics.

Publisher

MDPI AG

Subject

General Medicine

Reference50 articles.

1. 3D data management: Controlling data volume, velocity and variety;Laney;META Group Res. Note,2001

2. Big Data and the Future of Radiology Informatics

3. Concurrence of big data analytics and healthcare: A systematic review

4. Data mining with big data;Wu;IEEE Trans. Knowl. Data Eng.,2014

5. Volume and value of big healthcare data

Cited by 55 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine;Journal of Translational Medicine;2024-02-05

2. A Biobanking System for Diagnostic Images: Architecture Development, COVID-19–Related Use Cases, and Performance Evaluation;JMIR Formative Research;2023-12-21

3. Pipeline System for Versatile Medical Image Processing;2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology;2023-12-07

4. Exploring machine learning to hardware implementations for large data rate x-ray instrumentation;Machine Learning: Science and Technology;2023-11-24

5. A novel shape augmentation approach in training neural networks using Branch Length Similarity entropy;Physica A: Statistical Mechanics and its Applications;2023-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3