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Demography

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Active deep learning to detect demographic traits in free-form clinical notes.

Journal of biomedical informatics
The free-form portions of clinical notes are a significant source of information for research, but before they can be used, they must be de-identified to protect patients' privacy. De-identification efforts have focused on known identifier types (nam...

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Studies in health technology and informatics
Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine learning algorithms (Gradient Boosting, Random Forest, and Neural Network) for predicting the risk of...

Predicting geographic location from genetic variation with deep neural networks.

eLife
Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of kn...

Prediction of Patient Demographics using 3D Craniofacial Scans and Multi-view CNNs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
3D data is becoming increasingly popular and accessible for computer vision tasks. A popular format for 3D data is the mesh format, which can depict a 3D surface accurately and cost-effectively by connecting points in the (x, y, z) plane, known as ve...

EEG-based Depression Detection Using Convolutional Neural Network with Demographic Attention Mechanism.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalography (EEG)-based depression detection has become a hot topic in the development of biomedical engineering. However, the complexity and nonstationarity of EEG signals are two biggest obstacles to this application. In addition, the ge...

Predicting breast cancer risk using interacting genetic and demographic factors and machine learning.

Scientific reports
Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially fac...

Population demographics in geographic proximity to hospitals with robotic platforms do not correlate with disparities in access to robotic surgery.

Surgical endoscopy
BACKGROUND: Disparities in access to robotic surgery have been shown on the local, regional, and national level. This study aims to see if the location of hospitals with robotic platforms (HWR) correlates with population trends to explain the dispari...

Learning Bayesian networks from demographic and health survey data.

Journal of biomedical informatics
Child mortality from preventable diseases such as pneumonia and diarrhoea in low and middle-income countries remains a serious global challenge. We combine knowledge with available Demographic and Health Survey (DHS) data from India, to construct Cau...

Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning.

PLoS neglected tropical diseases
BACKGROUND: Dengue virus causes a wide spectrum of disease, which ranges from subclinical disease to severe dengue shock syndrome. However, estimating the risk of severe outcomes using clinical presentation or laboratory test results for rapid patien...

Reporting of demographic data and representativeness in machine learning models using electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. However, questions have arisen regarding biases in their development that can affect their applicability i...