AIMC Topic: Machine Learning

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Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

Journal of the American Medical Informatics Association : JAMIA
We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are ident...

NLPReViz: an interactive tool for natural language processing on clinical text.

Journal of the American Medical Informatics Association : JAMIA
The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary con...

Applying Machine Learning to Workers' Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011.

Journal of occupational and environmental medicine
OBJECTIVE: This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry.

Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions.

Journal for healthcare quality : official publication of the National Association for Healthcare Quality
A diverse universe of statistical models in the literature aim to help hospitals understand the risk factors of their preventable readmissions. However, these models are usually not necessarily applicable in other contexts, fail to achieve good discr...

A Systematic Review on Machine Learning in Neurosurgery: The Future of Decision-Making in Patient Care.

Turkish neurosurgery
Current practice of neurosurgery depends on clinical practice guidelines and evidence-based research publications that derive results using statistical methods. However, statistical analysis methods have some limitations such as the inability to anal...

Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.

Mini reviews in medicinal chemistry
The Machine Learning (ML) is one of the fastest developing techniques in the prediction and evaluation of important pharmacokinetic properties such as absorption, distribution, metabolism and excretion. The availability of a large number of robust va...

Predicting Hospitalization and Outpatient Corticosteroid Use in Inflammatory Bowel Disease Patients Using Machine Learning.

Inflammatory bowel diseases
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic disease characterized by unpredictable episodes of flares and periods of remission. Tools that accurately predict disease course would substantially aid therapeutic decision-making. This study...