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Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

JMIR Bioinformatics and Biotechnology(2023)10.2196/52059Source: DataRank Database

Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study is a research paper published in JMIR Bioinformatics and Biotechnology (2023). On theSindex it has a DataRank of 0. It has been cited 20 times.

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Open Access20 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)OA: goldTopics (26)IDs (PubMed)SDGs (1)

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Open Access

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Authors (8)

Alexa Dzienny ORCID,Mike Bopf,Jaclyn M. Phillips ORCID,Jerome J. Federspiel ORCID,Richard Amdur ORCID

Live enrichment

PubMed:38935950

National Institutes of Health

Grant: 5K23HL141640-04

Prevention of postpartum hemorrhage: identifying pregnant women at risk and determining the safe and effective use of tranexamic acid using state-of-the-art pharmacokinetic/pharmacodynamics modeling

National Institutes of Health

Grant: 5TL1TR002555-05

NRSA Training Core

goldLicense: http://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (http://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Bioinformatics and Biotechnology, is properly cited. The complete bibliographic information, a link to the original publication on http://bioinform.jmir.org/, as well as this copyright and license information must be included.

https://doi.org/10.2196/52059

https://pubmed.ncbi.nlm.nih.gov/38935950

http://dx.doi.org/10.2196/52059

https://doaj.org/article/da00788c1dfc4ed0bd16c96c99c79985

Fields of Study

03 medical and health sciences0302 clinical medicine

Keywords

PredictionBloodBleedingPredictTransfusionBirthObstetricsPostpartum hemorrhagehemorrhageGynecologyWomen's HealthMachine LearningAntepartumObstetricMaternalPostnatalPredictiveHemorrhagingGynecologicalOriginal PaperQH301-705.5Biology (General)TP248.13-248.65Biotechnology

Sustainable Development Goals

SDG 3: 3. Good health