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Blood Urea Nitrogen

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Estimating glucose requirements of an activated immune system in growing pigs.

Journal of animal science
Activated immune cells become obligate glucose utilizers, and a large i.v. lipopolysaccharide (LPS) dose causes insulin resistance and severe hypoglycemia. Therefore, study objectives were to quantify the amount of glucose needed to maintain euglycem...

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

Scientific reports
With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. Artificial intelligence models (AIs) like Gemini (Bard), Copilot (Bing), and ChatGPT-3.5 have the potential to impact every aspect of our lives, inclu...

Predictive markers of depression in hypertension.

Medicine
Hypertension and depression, as 2 major public health issues, are closely related. For patients having hypertension, in particular, depression is a risk factor for mortality and jeopardizes their wellbeing. The aim of the study is to apply support ve...

Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests.

JAMA network open
IMPORTANCE: Laboratory testing is an important target for high-value care initiatives, constituting the highest volume of medical procedures. Prior studies have found that up to half of all inpatient laboratory tests may be medically unnecessary, but...

Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.

Dialysis adequacy predictions using a machine learning method.

Scientific reports
Dialysis adequacy is an important survival indicator in patients with chronic hemodialysis. However, there are inconveniences and disadvantages to measuring dialysis adequacy by blood samples. This study used machine learning models to predict dialys...

Machine Learning-Based Mortality Prediction in Chronic Kidney Disease among Heart Failure Patients: Insights and Outcomes from the Jordanian Heart Failure Registry.

Medicina (Kaunas, Lithuania)
Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the quality of life of patients worldwide. Comorbidities such as chronic kidney disease (CKD), arterial hypert...

Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review.

Renal failure
BACKGROUND: With the development of artificial intelligence, the application of machine learning to develop predictive models for sepsis-associated acute kidney injury has made potential breakthroughs in early identification, grading, diagnosis, and ...

Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial.

European journal of clinical investigation
BACKGROUND: The prediction of ischaemic stroke in patients with heart failure with reduced ejection fraction (HFrEF) but without atrial fibrillation (AF) remains challenging. Our aim was to evaluate the performance of machine learning (ML) in identif...