Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training-Reference-Cited by-同舟云学术

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Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training

Published:2022-10-31 Issue:2 Volume:66 Page:118-127
ISSN:0933-7407
Container-title:Mycoses
language:en
Short-container-title:Mycoses

Author:

Wang Wei¹²^ORCID,Li Mujiao¹³,Fan Peimin⁴,Wang Hua⁵^ORCID,Cai Jing⁵^ORCID,Wang Kai⁵,Zhang Tao⁶,Xiao Zelin⁷,Yan Jingdong⁶,Chen Chaomin¹,Lv Qingwen²

Affiliation:

1. School of Biomedical Engineering Southern Medical University Guangzhou China

2. Department of Information, Zhujiang Hospital Southern Medical University Guangzhou China

3. Department of Information Guangzhou First People's Hospital Guangzhou China

4. Department of Information Center Guangzhou Chest Hospital Guangzhou China

5. Department of Critical Care Medicine Zhujiang Hospital, Southern Medical University Guangzhou China

6. Department of Information, Nanfang Hospital Southern Medical University Guangzhou China

7. Department of Surgery Guangzhou Chest Hospital Guangzhou China

Funder

National Key Research and Development Program of China

Publisher

Wiley

Subject

Infectious Diseases,Dermatology,General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/myc.13540

Reference28 articles.

1. Aspergillus Infections

2. Epidemiology of invasive fungal diseases on the basis of autopsy reports

3. Diagnosis and management of Aspergillus diseases: executive summary of the 2017 ESCMID-ECMM-ERS guideline

4. Executive Summary: Practice Guidelines for the Diagnosis and Management of Aspergillosis: 2016 Update by the Infectious Diseases Society of America

5. Point‐of‐care diagnosis of invasive aspergillosis in non‐neutropenic patients: Aspergillus Galactomannan Lateral Flow Assay versus Aspergillus ‐specific Lateral Flow Device test in bronchoalveolar lavage

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3. INTERPRETABLE MACHINE LEARNING FOR PREDICTING RISK OF INVASIVE FUNGAL INFECTION IN CRITICALLY ILL PATIENTS IN THE INTENSIVE CARE UNIT: A RETROSPECTIVE COHORT STUDY BASED ON MIMIC-IV DATABASE;Shock;2024-02-20

4. MI-DenseCFNet: deep learning–based multimodal diagnosis models for Aureus and Aspergillus pneumonia;European Radiology;2024-01-17

5. Supervised training models with or without manual lesion delineation outperform clinicians in distinguishing pulmonary cryptococcosis from lung adenocarcinoma on chest CT;Mycoses;2024-01

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