AIMC Topic: Machine Learning

Clear Filters Showing 33031 to 33040 of 34417 articles

Extracting Alcohol and Substance Abuse Status from Clinical Notes: The Added Value of Nursing Data.

Studies in health technology and informatics
We applied an open source natural language processing (NLP) system "NimbleMiner" to identify clinical notes with mentions of alcohol and substance abuse. NimbleMiner allows users to rapidly discover clinical vocabularies (using word embedding model) ...

Renal Biopsy Recommendation Based on Text Understanding.

Studies in health technology and informatics
Due to various etiologies and pathogenesis of kidney diseases, an invasive procedure called renal biopsy may be needed to determine the specific type of kidney disease, its severity, and the best treatment for it. This study aims to detmine if a text...

Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Studies in health technology and informatics
Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity...

Scoring Patient Fall Reports Using Quality Rubric and Machine Learning.

Studies in health technology and informatics
Patient falls, a subcategory of patient safety events, cause further harm and anxiety to patients in healthcare systems. Patient fall reports are a valuable resource to identify safety issues that demand further attention. Still, the main challenge f...

Development of Deep Learning Algorithm for Detection of Colorectal Cancer in EHR Data.

Studies in health technology and informatics
We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal cancer in Taiwanese adults. We collected data of 58152 patients from the Taiwan National Health Insurance database from 1999 to 2013. All patients' comorb...

Using Machine Learning to Integrate Socio-Behavioral Factors in Predicting Cardiovascular-Related Mortality Risk.

Studies in health technology and informatics
Cardiovascular disease is prevalent and associated with significant mortality rate. Robust lifetime risk stratification for cardiovascular disease is important for effective prevention, early diagnoses, targeted intervention, and improved prognosis. ...

Validating Auto-Suggested Changes for SNOMED CT in Non-Lattice Subgraphs Using Relational Machine Learning.

Studies in health technology and informatics
An attractive feature of non-lattice-based ontology auditing methods is its ability to not only identify potential quality issues, but also automatically generate the corresponding fixes. However, exhaustive manual evaluation of the validity of sugge...

Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers.

Studies in health technology and informatics
Clinical text de-identification enables collaborative research while protecting patient privacy and confidentiality; however, concerns persist about the reduction in the utility of the de-identified text for information extraction and machine learnin...

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice.

Studies in health technology and informatics
Frequent utilization of the Intensive Care Unit (ICU) is associated with higher costs and decreased availability for patients who urgently need it. Common risk assessment tool, like the ASA score, lack objectivity and do account only for some influen...

Interactive Machine Learning for Laboratory Data Integration.

Studies in health technology and informatics
Laboratory data collected in the electronic health record as part of routine care can be used in secondary research. For example, the US Department of Veterans Affairs maintains a data warehouse covering over 20 million individuals and 6.6 billion la...