AIMC Topic: United States

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A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

International journal of environmental research and public health
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB inci...

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning ha...

The practical implementation of artificial intelligence technologies in medicine.

Nature medicine
The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly, but real-world clinical implementation has not yet become a reality. Here we review some of the key practical issues surrounding the implementation o...

Constipation and risk of death and cardiovascular events.

Atherosclerosis
BACKGROUND AND AIMS: Constipation is one of the most frequent symptoms encountered in daily clinical practice and is implicated in the development of atherosclerosis, potentially through altered gut microbiota. However, little is known about its asso...

Review of water quality criteria for water reuse and risk-based implications for irrigated produce under the FDA Food Safety Modernization Act, produce safety rule.

Environmental research
Questions related to the safety of alternative water sources, such as recycled water or reclaimed water (including grey water, produced water, return flows, and recycled wastewater), for produce production have been largely un-explored at the detail ...

Predicting tumor cell line response to drug pairs with deep learning.

BMC bioinformatics
BACKGROUND: The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity.

Applying Machine Learning Algorithms to Segment High-Cost Patient Populations.

Journal of general internal medicine
BACKGROUND: Efforts to improve the value of care for high-cost patients may benefit from care management strategies targeted at clinically distinct subgroups of patients.