Can artificial intelligence predict the need for oxygen therapy in early stage COVID-19 pneumonia?

Abstract

This study investigated the utility of artificial intelligence in predicting disease progression. We analysed 194 patients with COVID-19 confirmed by reverse transcription polymerase chain reaction. Among them, 31 patients had oxygen therapy administered after admission. To assess the utility of artificial intelligence in the prediction of disease progression, we used three machine learning models employing clinical features (patient’s background, laboratory data, and symptoms), one deep learning model employing computed tomography (CT) images, and one multimodal deep learning model employing a combination of clinical features and CT images. We also evaluated the predictive values of these models and analysed the important features required to predict worsening in cases of COVID-19. The multimodal deep learning model had the highest accuracy. The CT image was an important feature of multimodal deep learning model. The area under the curve of all machine learning models employing clinical features and the deep learning model employing CT images exceeded 90%, and sensitivity of these models exceeded 95%. C-reactive protein and lactate dehydrogenase were important features of machine learning models. Our machine learning model, while slightly less accurate than the multimodal model, still provides a valuable medical triage tool for patients in the early stages of COVID-19.

Intelligent Fangcang Shelter Hospital Systems for Major Public Health Emergencies: The Case of the Optics Valley Fangcang Shelter Hospital

“…These data included CT images and clinical symptoms, as well as sleeping, breathing, and coughing status. Relying on a large amount of medical data and patient health data, the built-in learning algorithm of the cloud data platform can automatically analyze and remind doctors to assist in the diagnosis and treatment process, such as identifying the clinical type of the patients and predicting whether the patient will have severe disease symptoms which require more oxygen (Obinata et al 2020;Yan et al 2020). Multiple algorithms such as deep-learning models, artificial neural networks (ANN), and naive Bayes algorithms can be used (Jamshidi et al 2020;Mohanty et al 2020).…”