A transformer-based deep learning model for identifying the occurrence of acute hematogenous osteomyelitis and predicting blood culture results

Laboratory indicators, as easily accessible medical information, can identify osteomyelitis in pediatric patients. They can also predict whether pathogenic bacteria can be successfully cultured, regardless of whether the patient has received antibiotics beforehand. This not only simplifies the diagnostic process for pediatricians but also provides a basis for deciding whether to use empirical antibiotic therapy or discontinue treatment for blood cultures.

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Publication Details

Journal
Frontiers in Microbiology
Published
2024-11-06
DOI
https://doi.org/10.3389/fmicb.2024.1495709
Citations
7
Primary Topic
Orthopedic Infections and Treatments
Type
article
Field-Weighted Citation Impact
4.01
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article

A transformer-based deep learning model for identifying the occurrence of acute hematogenous osteomyelitis and predicting blood culture results

義典 橘高, Qiang Kang, Jiuhui Su, Yunhong Xia
7 citations
Frontiers in Microbiology
Orthopedic Infections and Treatments
4.01
article

A transformer-based deep learning model for identifying the occurrence of acute hematogenous osteomyelitis and predicting blood culture results

義典 橘高, Qiang Kang, Jiuhui Su, Yunhong Xia
article en
7 citations

Abstract

Laboratory indicators, as easily accessible medical information, can identify osteomyelitis in pediatric patients. They can also predict whether pathogenic bacteria can be successfully cultured, regardless of whether the patient has received antibiotics beforehand. This not only simplifies the diagnostic process for pediatricians but also provides a basis for deciding whether to use empirical antibiotic therapy or discontinue treatment for blood cultures.

Frontiers in MicrobiologyVol. 15
Dalian Medical University (CN), Second Affiliated Hospital of Dalian Medical University (CN), Inner Mongolia People's Hospital (CN), China Medical University (CN)
Good health and well-being
Openalex Percentile: Top 6%
Orthopedic Infections and Treatments
4.01
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