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ORIGINAL RESEARCH

A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information

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Pages 4083-4092 | Received 25 Jan 2023, Accepted 29 Apr 2023, Published online: 24 Jun 2023

References

  • Liu L, Johnson HL, Cousens S, et al. Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000. Lancet. 2012;379:2151–2161.
  • Jain S, Williams DJ, Arnold SR, et al. Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372:835–845. doi:10.1056/NEJMoa1405870
  • Wang H, Abajobir AA, Abate KH, et al. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;2017:1.
  • Jones RN. Microbial etiologies of hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia. Clin Infect Dis. 2010;51 Suppl 1:S81–S87. doi:10.1086/653053
  • Levy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10:S122–S129. doi:10.1038/nm1145
  • Donnelly JP, Baddley JW, Wang HE. Antibiotic utilization for acute respiratory tract infections in U.S. emergency departments. Antimicrob Agents Chemother. 2014;58:1451–1457. doi:10.1128/AAC.02039-13
  • Pervaiz F, Chavez MA, Ellington LE, et al. Building a prediction model for radiographically confirmed pneumonia in Peruvian children: from symptoms to imaging. Chest. 2018;154:1385–1394.
  • Yan C, Hui R, Lijuan Z, Zhou Y. Lung ultrasound vs. chest X-ray in children with suspected pneumonia confirmed by chest computed tomography: a retrospective cohort study. Exp Ther Med. 2020;19:1363–1369. doi:10.3892/etm.2019.8333
  • Edwards M, Lawson Z, Morris S, et al. The presence of radiological features on chest radiographs: how well do clinicians agree? Clin Radiol. 2012;67:664–668. doi:10.1016/j.crad.2011.12.003
  • Murdoch DR, O’Brien KL, Scott JA, et al. Breathing new life into pneumonia diagnostics. J Clin Microbiol. 2009;47:3405–3408. doi:10.1128/JCM.01685-09
  • Kratz AMP, Sullivan K, Gallagher J. Clinical impact of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for the management of inpatient pneumonia without additional antimicrobial stewardship support. Infect Control Hosp Epidemiol. 2019;40(9):1053–1055. doi:10.1017/ice.2019.191
  • Soomro TA, Zheng L, Afifi AJ, Ali A, Yin M, Gao J. Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research. Artif Intell Rev. 2022;55:1409–1439. doi:10.1007/s10462-021-09985-z
  • Shamman AH, Hadi AA, Ramul AR, Zahra MMA, Gheni HM. The artificial intelligence (AI) role for tackling against COVID-19 pandemic. Mater Today Proc. 2021;80:3663–3667. doi:10.1016/j.matpr.2021.07.357
  • L E, Zhao B, Guo Y, et al. Using deep-learning techniques for pulmonary-thoracic segmentations and improvement of pneumonia diagnosis in pediatric chest radiographs. Pediatr Pulmonol. 2019;54:1617–1626. doi:10.1002/ppul.24431
  • Rajpurkar P, Irvin J, Ball RL, et al. Deep learning for chest radiograph diagnosis: a retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med. 2018;15:e1002686. doi:10.1371/journal.pmed.1002686
  • Hwang EJ, Nam JG, Lim WH, et al. Deep learning for chest radiograph diagnosis in the emergency department. Radiology. 2019;293:573–580. doi:10.1148/radiol.2019191225
  • Wang J, Bao Y, Wen Y, et al. Prior-attention residual learning for more discriminative COVID-19 screening in CT images. IEEE Trans Med Imaging. 2020;39:2572–2583. doi:10.1109/TMI.2020.2994908
  • Xu GX, Liu C, Liu J, et al. Cross-site severity assessment of COVID-19 from CT images via domain adaptation. IEEE Trans Med Imaging. 2022;41:88–102. doi:10.1109/TMI.2021.3104474
  • Zhang M, Yu S, Yin X, et al. An AI-based auxiliary empirical antibiotic therapy model for children with bacterial pneumonia using low-dose chest CT images. Jpn J Radiol. 2021;39:973–983. doi:10.1007/s11604-021-01136-2
  • Xu M, Ouyang L, Han L, et al. Accurately differentiating between patients with COVID-19, patients with other viral infections, and healthy individuals: multimodal late fusion learning approach. J Med Internet Res. 2021;23:e25535. doi:10.2196/25535
  • Sheu RK, Chen LC, Wu CL, et al. Multi-modal data analysis for pneumonia status prediction using deep learning (MDA-PSP). Diagnostics. 2022;13:12. doi:10.3390/diagnostics13010012
  • Tan T, Das B, Soni R, et al. Multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19 using pristine ground-truth, versus radiologists. Neurocomputing. 2022;485:36–46. doi:10.1016/j.neucom.2022.02.040
  • Woan Ching SL, Lai KW, Chuah JH, et al. Multiclass convolution neural network for classification of COVID-19 CT images. Comput Intell Neurosci. 2022;2022:9167707. doi:10.1155/2022/9167707
  • Showkat S, Qureshi S. Efficacy of transfer learning-based ResNet models in chest X-ray image classification for detecting COVID-19 pneumonia. Chemometr Intell Lab Syst. 2022;224:104534. doi:10.1016/j.chemolab.2022.104534
  • Rasheed J, Shubair RM, Lunghi C, Dupuis D. Screening lung diseases using cascaded feature generation and selection strategies. Healthcare. 2022;11:10. doi:10.3390/healthcare11010010
  • Ksibi A, Zakariah M, Ayadi M, et al. Improved analysis of COVID-19 influenced pneumonia from the chest X-rays using fine-tuned residual networks. Comput Intell Neurosci. 2022;2022:9414567. doi:10.1155/2022/9414567
  • Dhiman G, Chang V, Kant Singh K, Shankar A. ADOPT: automatic deep learning and optimization-based approach for detection of novel coronavirus COVID-19 disease using X-ray images. J Biomol Struct Dyn. 2022;40:5836–5847. doi:10.1080/07391102.2021.1875049
  • Rangarajan AK, Ramachandran HK. A preliminary analysis of AI based smartphone application for diagnosis of COVID-19 using chest X-ray images. Expert Syst Appl. 2021;183:115401. doi:10.1016/j.eswa.2021.115401
  • Jia R, Yang J, Cui Y, Guo D, Li T. Gene expression analysis for pneumonia caused by Gram-positive bacterial infection. Exp Ther Med. 2018;15:3989–3996. doi:10.3892/etm.2018.5904
  • Agweyu A, Lilford RJ, English M; Clinical Information Network Author G. Appropriateness of clinical severity classification of new WHO childhood pneumonia guidance: a multi-hospital, retrospective, cohort study. Lancet Glob Health. 2018;6:e74–e83. doi:10.1016/S2214-109X(17)30448-5
  • van Vugt SF, Verheij TJ, de Jong PA, et al. Diagnosing pneumonia in patients with acute cough: clinical judgment compared to chest radiography. Eur Respir J. 2013;42:1076–1082. doi:10.1183/09031936.00111012
  • Valim C, Ahmad R, Lanaspa M, et al. Responses to bacteria, virus, and malaria distinguish the etiology of pediatric clinical pneumonia. Am J Respir Crit Care Med. 2016;193:448–459. doi:10.1164/rccm.201506-1100OC