AI Medical Compendium Journal:
Critical care medicine

Showing 41 to 45 of 45 articles

Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach.

Critical care medicine
OBJECTIVES: Identifying subgroups of ICU patients with similar clinical needs and trajectories may provide a framework for more efficient ICU care through the design of care platforms tailored around patients' shared needs. However, objective methods...

Patient-Specific Classification of ICU Sedation Levels From Heart Rate Variability.

Critical care medicine
OBJECTIVE: To develop a personalizable algorithm to discriminate between sedation levels in ICU patients based on heart rate variability.

Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

Critical care medicine
OBJECTIVE: The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability.

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

Critical care medicine
OBJECTIVE: Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter ...