دورية أكاديمية

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

التفاصيل البيبلوغرافية
العنوان: Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
المؤلفون: Yang Nan, Javier Del Ser, Simon Walsh, Carola Schonlieb, Michael Roberts, Ian Selby, Kit Howard, John Owen, Jon Neville, Julien Guiot, Benoit Ernst, Ana Pastor, Angel Alberich-Bayarri, Marion I. Menzel, Sean Walsh, Wim Vos, Nina Flerin, Jean-Paul Charbonnier, Eva van Rikxoort, Avishek Chatterjee, Henry Woodruff, Philippe Lambin, Leonor Cerda-Alberich, Luis Martí-Bonmatí, Francisco Herrera, Guang Yang
المصدر: Information Fusion
سنة النشر: 2022
المجموعة: Zenodo
مصطلحات موضوعية: data harmonisation, Information fusion, data standardisation, domain adaptation, reproducibility
الوصف: Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
العلاقة: info:eu-repo/grantAgreement/EC/H2020/101016131/; https://zenodo.org/communities/icovidTest; https://zenodo.org/record/7782100Test; https://doi.org/10.1016/j.inffus.2022.01.001Test; oai:zenodo.org:7782100
DOI: 10.1016/j.inffus.2022.01.001
الإتاحة: https://doi.org/10.1016/j.inffus.2022.01.001Test
https://zenodo.org/record/7782100Test
حقوق: info:eu-repo/semantics/openAccess ; https://creativecommons.org/licenses/by/4.0/legalcodeTest
رقم الانضمام: edsbas.33ADE75E
قاعدة البيانات: BASE