Dataset Information

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

ABSTRACT: During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

SUBMITTER: Shamout FE

PROVIDER: S-EPMC8115328 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

Shamout Farah E FE Shen Yiqiu Y Wu Nan N Kaku Aakash A Park Jungkyu J Makino Taro T Jastrzębski Stanisław S Witowski Jan J Wang Duo D Zhang Ben B Dogra Siddhant S Cao Meng M Razavian Narges N Kudlowitz David D Azour Lea L Moore William W Lui Yvonne W YW Aphinyanaphongs Yindalon Y Fernandez-Granda Carlos C Geras Krzysztof J KJ

NPJ digital medicine 20210512 1

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3661 patients, achieves an area under the receiver operating characte ...[more]

PMID: 33980980

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Dataset Information

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

Publications

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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