Big data research is everyone's research-Making epilepsy data science accessible to the global community: Report of the ILAE big data commission.

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-10-24 DOI:10.1002/epd2.20288
Colin B Josephson, Eleonora Aronica, Sandor Beniczky, Danielle Boyce, Gianpiero Cavalleri, Spiros Denaxas, Jacqueline French, Lara Jehi, Hyunyong Koh, Patrick Kwan, Carrie McDonald, James W Mitchell, Stefan Rampp, Lynette Sadleir, Sanjay M Sisodiya, Irene Wang, Samuel Wiebe, Clarissa Yasuda, Brett Youngerman
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Abstract

Epilepsy care generates multiple sources of high-dimensional data, including clinical, imaging, electroencephalographic, genomic, and neuropsychological information, that are collected routinely to establish the diagnosis and guide management. Thanks to high-performance computing, sophisticated graphics processing units, and advanced analytics, we are now on the cusp of being able to use these data to significantly improve individualized care for people with epilepsy. Despite this, many clinicians, health care providers, and people with epilepsy are apprehensive about implementing Big Data and accompanying technologies such as artificial intelligence (AI). Practical, ethical, privacy, and climate issues represent real and enduring concerns that have yet to be completely resolved. Similarly, Big Data and AI-related biases have the potential to exacerbate local and global disparities. These are highly germane concerns to the field of epilepsy, given its high burden in developing nations and areas of socioeconomic deprivation. This educational paper from the International League Against Epilepsy's (ILAE) Big Data Commission aims to help clinicians caring for people with epilepsy become familiar with how Big Data is collected and processed, how they are applied to studies using AI, and outline the immense potential positive impact Big Data can have on diagnosis and management.

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大数据研究是每个人的研究--让全球社会都能利用癫痫数据科学:国际癫痫协会大数据委员会的报告。
癫痫护理会产生多种来源的高维数据,包括临床、成像、脑电图、基因组学和神经心理学信息,这些数据会被例行收集,用于确定诊断和指导管理。得益于高性能计算、复杂的图形处理单元和先进的分析技术,我们现在即将能够利用这些数据显著改善癫痫患者的个性化护理。尽管如此,许多临床医生、医疗服务提供者和癫痫患者对实施大数据和人工智能(AI)等配套技术仍心存疑虑。实际问题、伦理问题、隐私问题和气候问题是尚未完全解决的现实而持久的担忧。同样,大数据和人工智能相关的偏见也有可能加剧地方和全球的差距。鉴于癫痫在发展中国家和社会经济贫困地区造成的高负担,这些问题与癫痫领域密切相关。这篇来自国际抗癫痫联盟(ILAE)大数据委员会的教育论文旨在帮助护理癫痫患者的临床医生熟悉大数据是如何收集和处理的,如何将它们应用到使用人工智能的研究中,并概述大数据可能对诊断和管理产生的巨大潜在积极影响。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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