Academic Journal

Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk

التفاصيل البيبلوغرافية
العنوان: Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk
Alternate Title: a scoping review protocol
المؤلفون: Seringa, Joana, Abreu, João, Magalhaes, Teresa
المساهمون: Centro de Investigação em Saúde Pública (CISP/PHRC), Comprehensive Health Research Centre (CHRC) - Pólo ENSP, Escola Nacional de Saúde Pública (ENSP), RUN
سنة النشر: 2024
مصطلحات موضوعية: Medicine(all)
الوصف: Funding Information: The present publication was funded by Funda\u00E7\u00E3o Ci\u00EAncia e Tecnologia, IP national support through CHRC (UIDP/04923/2020). Publisher Copyright: © Author(s) (or their employer(s)) 2024.
Description (Translated): Introduction Machine learning (ML) has emerged as a powerful tool for uncovering patterns and generating new information. In cardiology, it has shown promising results in predictive outcomes risk assessment of heart failure (HF) patients, a chronic condition affecting over 64 million individuals globally. This scoping review aims to synthesise the evidence on ML methods, applications and economic analysis to predict the HF hospitalisation risk. Methods and analysis This scoping review will use the approach described by Arksey and O’Malley. This protocol will use the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Protocol, and the PRISMA extension for scoping reviews will be used to present the results. PubMed, Scopus and Web of Science are the databases that will be searched. Two reviewers will independently screen the full-text studies for inclusion and extract the data. All the studies focusing on ML models to predict the risk of hospitalisation from HF adult patients will be included. Ethics and dissemination Ethical approval is not required for this review. The dissemination strategy includes peer-reviewed publications, conference presentations and dissemination to relevant stakeholders.
نوع الوثيقة: journal article
وصف الملف: application/pdf
اللغة: English
Relation: 2044-6055; PURE: 97676831
DOI: 10.1136/bmjopen-2023-083188
الاتاحة: http://hdl.handle.net/10362/170469
Rights: open access
رقم الانضمام: rcaap.com.unl.run.unl.pt.10362.170469
قاعدة البيانات: RCAAP
الوصف
DOI:10.1136/bmjopen-2023-083188