Mini-review of clinical data service platforms in the era of artificial intelligence: A case study of the iHi data platform.

IF 2.1 Q2 MEDICINE, GENERAL & INTERNAL
BioMedicine-Taiwan Pub Date : 2025-03-01 eCollection Date: 2025-01-01 DOI:10.37796/2211-8039.1643
Yu-Ting Lin, Ya-Chi Lin, Hung-Lin Chen, Che-Chen Lin, Min-Yen Wu, Sheng-Hsuan Chen, Zi-Han Lin, Yi-Ching Chang, Chuan-Hu Sun, Sheng-Ya Lu, Min-Yu Chiang, Hui-Chao Tsai, Mei-Ju Shih, David Ray Chang, Fuu-Jen Tsai, Hsiu-Yin Chiang, Chin-Chi Kuo
{"title":"Mini-review of clinical data service platforms in the era of artificial intelligence: A case study of the iHi data platform.","authors":"Yu-Ting Lin, Ya-Chi Lin, Hung-Lin Chen, Che-Chen Lin, Min-Yen Wu, Sheng-Hsuan Chen, Zi-Han Lin, Yi-Ching Chang, Chuan-Hu Sun, Sheng-Ya Lu, Min-Yu Chiang, Hui-Chao Tsai, Mei-Ju Shih, David Ray Chang, Fuu-Jen Tsai, Hsiu-Yin Chiang, Chin-Chi Kuo","doi":"10.37796/2211-8039.1643","DOIUrl":null,"url":null,"abstract":"<p><p>In the past two decades, healthcare organizations have transitioned from the early stages of digitization and digitalization to a more comprehensive process of digital transformation, a shift significantly accelerated by the advent of artificial intelligence (AI). Consequently, the development of high-quality clinical data warehouses, derived from electronic health records (EHRs) and enriched with multidomain data, such as genomics, proteomics, and Internet of Things (IoT) information, has become essential for the creation of the modern patient digital twin (PDT). This approach is critical for leveraging AI in the evolving landscape of clinical practice. Leading medical centers and healthcare institutions have adopted this model, as summarized in this review. Since 2020, China Medical University Hospital (CMUH) has been constructing its data ecosystem by integrating EHRs with extensive genomic databases. This initiative has led to the development of a data service platform, the ignite Hyper-intelligence (iHi®) platform. The iHi platform serves as a case study exemplifying the workflow of the smart data chip, which facilitates the deep cleaning and reliable de-identification of clinical data while incorporating analytical platforms related to genomics and the microbiome to enhance insight extraction processes. The ability to predict complex interactions and disease trajectories among PDTs, digital counterparts of healthcare professionals, and virtual socioeconomic environments will be pivotal in advancing personalized healthcare and optimizing patient outcomes. Future challenges will involve the unification of cross-institutional data platforms and ensuring the interoperability of AI inferences-key factors that will define the next era of AI-driven healthcare.</p>","PeriodicalId":51650,"journal":{"name":"BioMedicine-Taiwan","volume":"15 1","pages":"6-22"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11959964/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BioMedicine-Taiwan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37796/2211-8039.1643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

Abstract

In the past two decades, healthcare organizations have transitioned from the early stages of digitization and digitalization to a more comprehensive process of digital transformation, a shift significantly accelerated by the advent of artificial intelligence (AI). Consequently, the development of high-quality clinical data warehouses, derived from electronic health records (EHRs) and enriched with multidomain data, such as genomics, proteomics, and Internet of Things (IoT) information, has become essential for the creation of the modern patient digital twin (PDT). This approach is critical for leveraging AI in the evolving landscape of clinical practice. Leading medical centers and healthcare institutions have adopted this model, as summarized in this review. Since 2020, China Medical University Hospital (CMUH) has been constructing its data ecosystem by integrating EHRs with extensive genomic databases. This initiative has led to the development of a data service platform, the ignite Hyper-intelligence (iHi®) platform. The iHi platform serves as a case study exemplifying the workflow of the smart data chip, which facilitates the deep cleaning and reliable de-identification of clinical data while incorporating analytical platforms related to genomics and the microbiome to enhance insight extraction processes. The ability to predict complex interactions and disease trajectories among PDTs, digital counterparts of healthcare professionals, and virtual socioeconomic environments will be pivotal in advancing personalized healthcare and optimizing patient outcomes. Future challenges will involve the unification of cross-institutional data platforms and ensuring the interoperability of AI inferences-key factors that will define the next era of AI-driven healthcare.

人工智能时代临床数据服务平台小回顾——以iHi数据平台为例
在过去二十年中,医疗机构已从数字化和数字化的早期阶段过渡到更全面的数字化转型过程,人工智能(AI)的出现大大加速了这一转变。因此,开发源于电子健康记录(EHR)并丰富了基因组学、蛋白质组学和物联网(IoT)信息等多域数据的高质量临床数据仓库,已成为创建现代患者数字孪生(PDT)的关键。这种方法对于在不断发展的临床实践中利用人工智能至关重要。领先的医疗中心和医疗机构已经采用了这种模式,本综述对此进行了总结。自 2020 年以来,中国医科大学附属医院(CMUH)一直在通过整合电子病历和广泛的基因组数据库来构建其数据生态系统。这一举措促成了数据服务平台--点燃超智能(iHi®)平台的开发。iHi 平台是智能数据芯片工作流程的一个案例研究,它有助于对临床数据进行深度清理和可靠的去标识化,同时结合与基因组学和微生物组相关的分析平台,加强洞察力提取过程。预测PDT、医疗保健专业人员的数字对应方以及虚拟社会经济环境之间复杂的相互作用和疾病轨迹的能力,对于推进个性化医疗保健和优化患者预后至关重要。未来的挑战将涉及跨机构数据平台的统一以及确保人工智能推断的互操作性--这些关键因素将决定下一个人工智能驱动的医疗保健时代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
BioMedicine-Taiwan
BioMedicine-Taiwan MEDICINE, GENERAL & INTERNAL-
CiteScore
2.80
自引率
5.90%
发文量
21
审稿时长
24 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信