Publication detail

Corticosteroid Treatment Prediction using Chest X-ray and Clinical Data

MEZINA, A. GENZOR, S. BURGET, R. MYŠKA, V. MIZERA, J. OMETOV, A.

Original Title

Corticosteroid Treatment Prediction using Chest X-ray and Clinical Data

Type

journal article in Web of Science

Language

English

Original Abstract

Background and Objective: Severe courses of COVID-19 disease can lead to long-term complications. The post-acute phase of COVID-19 refers to the persistent or new symptoms. This problem is becoming more relevant with the increasing number of patients who have contracted COVID-19 and the emergence of new virus variants. In this case, preventive treatment with corticosteroids can be applied. However, not everyone benefits from the treatment, moreover, it can have severe side effects. Currently, no study would analyze who benefits from the treatment. Methods: This work introduces a novel approach to the recommendation of Corticosteroid (CS) treatment for patients in the post-acute phase. We have used a novel combination of clinical data, including blood tests, spirometry, and X-ray images from 273 patients. These are very challenging to collect, especially from patients in the post-acute phase of COVID-19. To our knowledge, no similar dataset exists in the literature. Moreover, we have proposed a unique methodology that combines machine learning and deep learning models based on Vision Transformer (ViT) and InceptionNet, preprocessing techniques, and pretraining strategies to deal with the specific characteristics of our data. Results: The experiments have proved that combining clinical data with CXR images achieves 8% higher accuracy than independent analysis of CXR images. The proposed method reached 80.0% accuracy (78.7% balanced accuracy) and a ROC-AUC of 0.89. Conclusions: The introduced system for CS treatment prediction using our neural network and learning algorithm is unique in this field of research. Here, we have shown the efficiency of using mixed data and proved it on real-world data. The paper also introduces the factors that could be used to predict long-term complications. Additionally, this system was deployed to the hospital environment as a recommendation tool, which admits the clinical application of the proposed methodology.

Keywords

Image classification; Chest X-ray images; Vision transformer; Treatment prediction; Clinical data; Post-acute COVID-19

Authors

MEZINA, A.; GENZOR, S.; BURGET, R.; MYŠKA, V.; MIZERA, J.; OMETOV, A.

Released

2. 12. 2024

Publisher

Elsevier

ISBN

2001-0370

Periodical

Computational and Structural Biotechnology Journal

Year of study

24

Number

December 24

State

Kingdom of Sweden

Pages from

53

Pages to

65

Pages count

13

URL

https://www.sciencedirect.com/science/article/pii/S2001037023004713

Full text in the Digital Library

http://hdl.handle.net/11012/245188

BibTex

@article{BUT185577,
  author="Anzhelika {Mezina} and Samuel {Genzor} and Radim {Burget} and Vojtěch {Myška} and Jan {Mizera} and Aleksandr {Ometov}",
  title="Corticosteroid Treatment Prediction using Chest X-ray and Clinical Data",
  journal="Computational and Structural Biotechnology Journal",
  year="2024",
  volume="24",
  number="December 24",
  pages="53--65",
  doi="10.1016/j.csbj.2023.11.057",
  issn="2001-0370",
  url="https://www.sciencedirect.com/science/article/pii/S2001037023004713"
}