Literature DB >> 24046473

Predictive models in heart failure: who cares?

Robert M Califf1, Michael J Pencina.   

Abstract

Entities:  

Keywords:  Editorials; decision support techniques; heart failure; models, decision support; models, statistical

Mesh：

Year:  2013        PMID： 24046473     DOI： 10.1161/CIRCHEARTFAILURE.113.000659

Source DB:  PubMed          Journal:  Circ Heart Fail        ISSN： 1941-3289            Impact factor:   8.790


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  3 in total

Review 1.  Clinical Prediction Models for Heart Failure Hospitalization in Type 2 Diabetes: A Systematic Review and Meta-Analysis.

Authors:  Amir Razaghizad; Emily Oulousian; Varinder Kaur Randhawa; João Pedro Ferreira; James M Brophy; Stephen J Greene; Julian Guida; G Michael Felker; Marat Fudim; Michael Tsoukas; Tricia M Peters; Thomas A Mavrakanas; Nadia Giannetti; Justin Ezekowitz; Abhinav Sharma
Journal:  J Am Heart Assoc       Date:  2022-05-16       Impact factor: 6.106

2.  Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

Authors:  Vahid Taslimitehrani; Guozhu Dong; Naveen L Pereira; Maryam Panahiazar; Jyotishman Pathak
Journal:  J Biomed Inform       Date:  2016-02-01       Impact factor: 6.317

3.  Validation of the myocardial-ischaemic-injury-index machine learning algorithm to guide the diagnosis of myocardial infarction in a heterogenous population: a prespecified exploratory analysis.

Authors:  Dimitrios Doudesis; Kuan Ken Lee; Jason Yang; Ryan Wereski; Anoop S V Shah; Athanasios Tsanas; Atul Anand; John W Pickering; Martin P Than; Nicholas L Mills
Journal:  Lancet Digit Health       Date:  2022-05
  3 in total

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