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Mortality

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Selection and Short-Term Outcomes of Living Kidney Donors in Singapore - An Analysis of the Donor Care Registry.

Annals of the Academy of Medicine, Singapore
INTRODUCTION: Transplant rates in Singapore have been falling and there is limited information on baseline characteristics and clinical outcomes of living kidney donors nationally. This study aimed to determine the safety of living kidney donor trans...

The effects of deep network topology on mortality prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attenti...

Prediction using patient comparison vs. modeling: a case study for mortality prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application o...

AIDS causes sharp rise in number of Brazilian orphans.

AIDS weekly plus
An estimated 183,000 Brazilian children are at risk of losing their mothers to AIDS, according to a survey released. The survey, sponsored by UNICEF, was conducted by the John Snow Institute. Survey estimates are that 10,600 Brazilian children younge...

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

Statistics in medicine
Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predicti...

Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework.

Scientific reports
Precision medicine approaches rely on obtaining precise knowledge of the true state of health of an individual patient, which results from a combination of their genetic risks and environmental exposures. This approach is currently limited by the lac...

Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

BMC medical informatics and decision making
BACKGROUND: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into p...