AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Critical Care

Showing 191 to 200 of 273 articles

Clear Filters

High-Dose Vitamin D Administration Is Associated With Increases in Hemoglobin Concentrations in Mechanically Ventilated Critically Ill Adults: A Pilot Double-Blind, Randomized, Placebo-Controlled Trial.

JPEN. Journal of parenteral and enteral nutrition
BACKGROUND: Anemia and vitamin D deficiency are highly prevalent in critical illness, and vitamin D status has been associated with hemoglobin concentrations in epidemiologic studies. We examined the effect of high-dose vitamin D therapy on hemoglobi...

Evaluation of an automated knowledge-based textual summarization system for longitudinal clinical data, in the intensive care domain.

Artificial intelligence in medicine
OBJECTIVES: To examine the feasibility of the automated creation of meaningful free-text summaries of longitudinal clinical records, using a new general methodology that we had recently developed; and to assess the potential benefits to the clinical ...

Learning representations for the early detection of sepsis with deep neural networks.

Computers in biology and medicine
BACKGROUND: Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens.

Comparative Simulation Study of Glucose Control Methods Designed for Use in the Intensive Care Unit Setting via a Novel Controller Scoring Metric.

Journal of diabetes science and technology
BACKGROUND: Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates and thereby decrease health care expenditures. To evaluate what constitutes effective glucose control, typicall...

Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Critical care patient events like sepsis or septic shock in intensive care units (ICUs) are dangerous complications which can cause multiple organ failures and eventual death. Preventive prediction of such events will allow ...

Ultrasound-Assessed Gastric Antral Area Correlates With Aspirated Tube Feed Volume in Enterally Fed Critically Ill Patients.

Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
BACKGROUND: Enteral tube feed (ETF) intolerance occurs frequently in hospitalized patients and more so in critically ill patients. Most critical care nurses continue to assess gastric residual volume (GRV), especially among those with a history of ET...

A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series.

IEEE journal of biomedical and health informatics
Physiological variables, such as heart rate (HR), blood pressure (BP) and respiration (RESP), are tightly regulated and coupled under healthy conditions, and a break-down in the coupling has been associated with aging and disease. We present an appro...

Reduction of false arrhythmia alarms using signal selection and machine learning.

Physiological measurement
In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm is true or false. The large number of false alarms in intensive care is a severe issue. The noise peaks caused by alarms can be high and in a noisy en...