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Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive perform...

Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive perform...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f075b261cadc4b909376e8bceccb2f25

Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance

About this item

Full title

Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance

Publisher

London: Nature Publishing Group UK

Journal title

NPJ digital medicine, 2020-10, Vol.3 (1), p.139-139, Article 139

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Acute kidney injury (AKI) is a major complication after cardiothoracic surgery. Early prediction of AKI could prompt preventive measures, but is challenging in the clinical routine. One important reason is that the amount of postoperative data is too massive and too high-dimensional to be effectively processed by the human operator. We therefore so...

Alternative Titles

Full title

Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_f075b261cadc4b909376e8bceccb2f25

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f075b261cadc4b909376e8bceccb2f25

Other Identifiers

ISSN

2398-6352

E-ISSN

2398-6352

DOI

10.1038/s41746-020-00346-8

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