The value of longitudinal clinical data and paired CT scans in predicting the deterioration of COVID-19 revealed by an artificial intelligence system

Han, Xiaoyang; Yu, Ziqi; Zhuo, Yaoyao; Zhao, Bingjie; Ren, Yan; Lamm, Lorenz; Xue, Xiangyang; Feng, Jianfeng; Marr, Carsten; Shan, Fei; Peng, Tingying; Zhang, Xiao‐Yong

doi:10.1016/j.isci.2022.104227

Cited by 8 publications

(4 citation statements)

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“…A combination of both longitudinal and clinical data yielded a performance increase to an AUC of 0.727 and an accuracy of 0.732. The study in [ 143 ] examined the progression of COVID-19 severity over time using longitudinal CT and clinical data. The data set consisted of 119 COVID-19 patients with 341 longitudinal CT scans from the Shanghai Public Health Clinical Center.…”

Section: Covid-19 Prognostic and Longitudinal Modelsmentioning

confidence: 99%

A Comprehensive Review of Machine Learning Used to Combat COVID-19

et al. 2022

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Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19. In this research, we review these modern tools deployed to solve a variety of complex problems. We explore research that focused on analyzing medical images using AI models for identification, classification, and tissue segmentation of the disease. We also explore prognostic models that were developed to predict health outcomes and optimize the allocation of scarce medical resources. Longitudinal studies were conducted to better understand COVID-19 and its effects on patients over a period of time. This comprehensive review of the different AI methods and modeling efforts will shed light on the role that AI has played and what path it intends to take in the fight against COVID-19.

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Section: Covid-19 Prognostic and Longitudinal Modelsmentioning

confidence: 99%

A Comprehensive Review of Machine Learning Used to Combat COVID-19

et al. 2022

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“…Some studies have recently reported an AI model, the so-called bimodal model, that can analyze data integrated from medical images and patient information. 10 , 11 , 12 If patient information is combined successfully, the bimodal model has the potential to outperform the previous unimodal model that analyzes images alone. 10 , 11 , 12 …”

Section: Introductionmentioning

confidence: 99%

“… 10 , 11 , 12 If patient information is combined successfully, the bimodal model has the potential to outperform the previous unimodal model that analyzes images alone. 10 , 11 , 12 …”

Section: Introductionmentioning

confidence: 99%

“… 13 , 14 , 15 Furthermore, previous studies discussing bimodal AI in medicine used models combining GBDT and a convolutional neural network (CNN). 10 , 11 Recently, the Google Cloud AI research team invented TabNet as a state-of-the-art deep learning model for tabular data 16 and TabNet has been shown to be more effective than GBDT in a variety of tasks such as classification of forest cover type and the poker hand. 16 , 17 Additionally, TabNet has been applied in the medical field.…”

Section: Introductionmentioning

confidence: 99%

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