AI Medical Compendium Topic:
SARS-CoV-2

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eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19.

PloS one
We present an interpretable machine learning algorithm called 'eARDS' for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-hours before satisfying the Berlin clinical criteria. The analysis was conducted on data collected f...

A New Approach to Predicting Cryptocurrency Returns Based on the Gold Prices with Support Vector Machines during the COVID-19 Pandemic Using Sensor-Related Data.

Sensors (Basel, Switzerland)
In a real-world situation produced under COVID-19 scenarios, predicting cryptocurrency returns accurately can be challenging. Such a prediction may be helpful to the daily economic and financial market. Unlike forecasting the cryptocurrency returns, ...

Robots in Healthcare? What Patients Say.

International journal of environmental research and public health
In this paper, we analyse patients' perspectives on the introduction of artificial intelligence (AI) and robotic systems in healthcare. Based on citizens' experiences when hospitalised for COVID-19, we explore how the opinions and concerns regarding ...

Loan default prediction of Chinese P2P market: a machine learning methodology.

Scientific reports
Repayment failures of borrowers have greatly affected the sustainable development of the peer-to-peer (P2P) lending industry. The latest literature reveals that existing risk evaluation systems may ignore important signals and risk factors affecting ...

Diagnostic Test Accuracy of Deep Learning Detection of COVID-19: A Systematic Review and Meta-Analysis.

Academic radiology
RATIONALE AND OBJECTIVE: To perform a meta-analysis to compare the diagnostic test accuracy (DTA) of deep learning (DL) in detecting coronavirus disease 2019 (COVID-19), and to investigate how network architecture and type of datasets affect DL perfo...

Federated learning for predicting clinical outcomes in patients with COVID-19.

Nature medicine
Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe ...

[Digitization of the healthcare system: the BfArM's contribution to the development of potential].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Digitalization is a clear megatrend of our time, also in the health sector, which is currently experiencing enormous acceleration due to the COVID-19 pandemic in addition to paving the way due to changes in the legal framework. Looking to the future,...

Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-19, there is a noticeable shortage of literature dealing with ML usage in prediction of disease seve...

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs.

The British journal of radiology
OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor prognosis as defined by the need for intensive unit care and mechanical ventilation. We tested the fea...

SIRVD-DL: A COVID-19 deep learning prediction model based on time-dependent SIRVD.

Computers in biology and medicine
COVID-19 is one of the biggest challenges that human beings have faced recently. Many researchers have proposed different prediction methods for establishing a virus transmission model and predicting the trend of COVID-19. Among them, the methods bas...