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Clinical and inflammatory features based machine learning model for fatal risk prediction of hospitalized COVID-19 patie...

Published in Annals of medicine

To appraise effective predictors for COVID-19 mortality in a retrospective cohort study. A total of 1270 COVID-19 patients, including 984 admitted in Sino French New City Branch (training and internal validation sets randomly split at 7:3 ratio) and 286 admitted in Optical Valley Branch (external validation set) of Wuhan Tongji hospital, were inclu...

Improving Ultrawide Band Ranging Using Two Antennas

Ultrawideband technology can be used to measure the distance between two device equipped with ultrawideband transceivers. Multiple ultrawideband devices known as anchors can localize a device that supports ultrawideband communication after each anchor measures the distance between itself and the device. The anchor and the tag can measure the distan...

Predicting Flight Delay Distributions: A Machine Learning-Based Approach at a Regional Airport

In an effort to improve an airport operation optimization model, this research investigates the possibility of predicting probability distributions of flight delays with machine learning algorithms. The research is centered around Rotterdam The Hague Airport, a regional airport in the Netherlands. The first objective is to test how well machine lea...

High-dimensional numerical optimization of fiber reinforced polymers with variational autoencoders and Bayesian optimiza...

Designing engineering structures relies on accurate numerical simulations to predict the behaviour of a structure before its realization. In the design process, many variables influence the final structure. There is an incentive for optimizing the design based on the desire for cheaper structures and less material usage. Although a wide variety of ...

Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records...

Published in JMIR medical informatics

Postoperative length of stay is a key indicator in the management of medical resources and an indirect predictor of the incidence of surgical complications and the degree of recovery of the patient after cancer surgery. Recently, machine learning has been used to predict complex medical outcomes, such as prolonged length of hospital stay, using ext...

Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset....

Published in Journal of the American Medical Informatics Association : JAMIA

The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. We used the ...