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Complex overlapping concepts: An effective auditing methodology for families of similarly structured BioPortal ontologies.

Journal of biomedical informatics
In previous research, we have demonstrated for a number of ontologies that structurally complex concepts (for different definitions of "complex") in an ontology are more likely to exhibit errors than other concepts. Thus, such complex concepts often ...

Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this ris...

ProvCaRe Semantic Provenance Knowledgebase: Evaluating Scientific Reproducibility of Research Studies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Scientific reproducibility is critical for biomedical research as it enables us to advance science by building on previous results, helps ensure the success of increasingly expensive drug trials, and allows funding agencies to make informed decisions...

Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Advanced regression and machine learning models can provide personalized risk predictions to support clinical decision-making. We aimed to understand whether modeling methods impact the tendency of calibration to deteriorate as patient populations sh...

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

Journal of medical systems
Diabetes mellitus is a group of metabolic diseases in which blood sugar levels are too high. About 8.8% of the world was diabetic in 2017. It is projected that this will reach nearly 10% by 2045. The major challenge is that when machine learning-base...

Word embeddings quantify 100 years of gender and ethnic stereotypes.

Proceedings of the National Academy of Sciences of the United States of America
Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we de...

Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network.

Scientific reports
Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may help save lives. In this paper, we use the Twitter data set and the United States Centers for Disea...

Predictors of firearm violence in urban communities: A machine-learning approach.

Health & place
Interpersonal firearm violence is a leading cause of death and injuries in the United States. Identifying community characteristics associated with firearm violence is important to improve confounder selection and control in health research, to bette...

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

Health services research
OBJECTIVE: To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending.