Testing the performance, adequacy, and applicability of an artificial intelligence model for pediatric pneumonia diagnosis-Reference-Cited by-同舟云学术

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Testing the performance, adequacy, and applicability of an artificial intelligence model for pediatric pneumonia diagnosis

Published:2023-12 Issue: Volume:242 Page:107765
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Domínguez-Rodríguez Sara,Liz-López Helena,Panizo-LLedot Angel,Ballesteros Álvaro,Dagan Ron,Greenberg David,Gutiérrez Lourdes,Rojo Pablo,Otheo Enrique,Galán Juan Carlos,Villanueva Sara,García Sonsoles,Mosquera Pablo,Tagarro Alfredo,Moraleda Cinta,Camacho David

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference45 articles.

1. «Reliability of radiographic findings and the relation to etiologic agents in community-acquired pneumonia»;Boersma;Respir. Med.,2006

2. «Standardized interpretation of paediatric chest radiographs for the diagnosis of pneumonia in epidemiological studies»;Cherian;Bull. World Health Organ.,2005

3. «The need to look at antibiotic resistance from a health systems perspective»;Tomsony;Upsala J. Med. Sci.,2014

4. «A survey on deep learning in medicine: why, how and when?»;Piccialli;Inf. Fusion,2021

5. «Identifying pneumonia in chest X-rays: a deep learning approach»;Jaiswal;Measurement,2019

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