IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung cancer cohort assembled from EHR data would be a powerful platform for clinical outcome studies.
Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challenging the development of new therapeutics for brain disorders. Transcardial perfusion is instrumental for removing the intravascular fraction of an in...
Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the mechanism of disease development is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of AD's...
Bovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms...
BMC medical informatics and decision making
Jul 1, 2021
BACKGROUND: In Chile, a patient needing a specialty consultation or surgery has to first be referred by a general practitioner, then placed on a waiting list. The Explicit Health Guarantees (GES in Spanish) ensures, by law, the maximum time to solve ...
Computational intelligence and neuroscience
Jul 1, 2021
The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper different machine learning algorithms and deep learning are applied to compare the results and analysis o...
Machine learning models have increasingly been used in bankruptcy prediction. However, the observed historical data of bankrupt companies are often affected by data imbalance, which causes incorrect prediction, resulting in substantial economic losse...
PURPOSE: To facilitate the demonstration of the prognostic value of radiomics, multicenter radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis is however challenging, as they are sensitive to the variability...
Advances in artificial intelligence and machine learning have fueled growing interest in the application of predictive analytics to identify high-risk suicidal patients. Such application will require the aggregation of large-scale, sensitive patient ...
Artificial intelligence (AI) represents a broad category of algorithms for which deep learning is currently the most impactful. When electing to begin the process of building an adequate fundamental knowledge base allowing them to decipher machine le...
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