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Incidence

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Identification of risk features for complication in Gaucher's disease patients: a machine learning analysis of the Spanish registry of Gaucher disease.

Orphanet journal of rare diseases
BACKGROUND: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at ris...

Prediction of hepatitis E using machine learning models.

PloS one
BACKGROUND: Accurate and reliable predictions of infectious disease can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task. Howev...

Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.

Radiologic clinics of North America
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

Journal of medical Internet research
BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suit...

Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.

Improving disaggregation models of malaria incidence by ensembling non-linear models of prevalence.

Spatial and spatio-temporal epidemiology
Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable routine surveillance data of malaria incidence, typically aggregated to administrative units, is becoming more widely available. Disaggregation regress...

Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults.

PloS one
BACKGROUND: Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many fal...