AIMC Topic: United States

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Breaking down the silos of artificial intelligence in surgery: glossary of terms.

Surgical endoscopy
BACKGROUND: The literature on artificial intelligence (AI) in surgery has advanced rapidly during the past few years. However, the published studies on AI are mostly reported by computer scientists using their own jargon which is unfamiliar to surgeo...

Prediction Performance of Deep Learning for Colon Cancer Survival Prediction on SEER Data.

BioMed research international
Colon and rectal cancers are the most common kinds of cancer globally. Colon cancer is more prevalent in men than in women. Early detection increases the likelihood of survival, and treatment significantly increases the likelihood of eradicating the ...

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis.

PloS one
There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conduc...

Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration.

Annual review of biomedical data science
Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by elec...

NeoAI 1.0: Machine learning-based paradigm for prediction of neonatal and infant risk of death.

Computers in biology and medicine
BACKGROUND: The Neonatal mortality rate in the United States is 3.8 deaths per 1000 live births, which is comparably higher than other nations.

Developing Acute Event Risk Profiles for Older Adults with Dementia in Long-Term Care Using Motor Behavior Clusters Derived from Deep Learning.

Journal of the American Medical Directors Association
OBJECTIVES: This paper uses deep (machine) learning techniques to develop and test how motor behaviors, derived from location and movement sensor tracking data, may be associated with falls, delirium, and urinary tract infections (UTIs) in long-term ...

Computed Tomography Images under Artificial Intelligence Algorithms on the Treatment Evaluation of Intracerebral Hemorrhage with Minimally Invasive Aspiration.

Computational and mathematical methods in medicine
The aim of this study was to investigate the therapeutic effect of minimally invasive aspiration on intracerebral hemorrhage (ICH) and the value of artificial intelligence algorithm combined with computed tomography (CT) image evaluation. Ninety-two ...

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...

A scholarly network of AI research with an information science focus: Global North and Global South perspectives.

PloS one
This paper primarily aims to provide a citation-based method for exploring the scholarly network of artificial intelligence (AI)-related research in the information science (IS) domain, especially from Global North (GN) and Global South (GS) perspect...

Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.

IEEE journal of biomedical and health informatics
Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical for public health, especially during the COVID-19 pandemic, as institutions and government a...