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Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.

Computers, informatics, nursing : CIN
Although machine learning is increasingly being applied to support clinical decision making, there is a significant gap in understanding what it is and how nurses should adopt it in practice. The purpose of this case study is to show how one applicat...

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

The Journal of antimicrobial chemotherapy
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...

The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.

Neuroinformatics
A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be dire...

Discovery of Distinct Immune Phenotypes Using Machine Learning in Pulmonary Arterial Hypertension.

Circulation research
RATIONALE: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) and therapies targeting immunity are under investigation, although it remains unknown if distinct immune phenotypes exist.

Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Journal of the American Heart Association
Background The ability to accurately predict the occurrence of in-hospital death after percutaneous coronary intervention is important for clinical decision-making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System...

Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.

Journal of the American Heart Association
Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learning technique called Bayesian Additive Regression Trees ( BART ). Methods and Results This analysis included 4714 participants from MESA (Multi-Ethnic S...

A deep learning algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker and reverberation.

The Journal of the Acoustical Society of America
For deep learning based speech segregation to have translational significance as a noise-reduction tool, it must perform in a wide variety of acoustic environments. In the current study, performance was examined when target speech was subjected to in...

Predicting Future Cardiovascular Events in Patients With Peripheral Artery Disease Using Electronic Health Record Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Patients with peripheral artery disease (PAD) are at risk of major adverse cardiac and cerebrovascular events. There are no readily available risk scores that can accurately identify which patients are most likely to sustain an event, mak...