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Hospitalization

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Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognostic accuracy in test datasets, but little is known about their embedding into clinical workflows. We implemented a random forest-based algorithm to iden...
Electronic Health Records Female Hospitalization Aged Machine Learning Algorithms Prospective Studies ROC Curve Models, Theoretical Workflow Delirium Aged, 80 and over Male Middle Aged Risk Assessment Humans
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Neural Networks for Cause of Hospitalization and Final Cause of Death Extraction from Discharge Summaries.

Studies in health technology and informatics Jun 16, 2020
Determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost importance. This is usually recorded in free text form. In this study we aimed to develop a series of supervised natural language processing algorith...
Humans Neural Networks, Computer Hospitalization Natural Language Processing Cause of Death Patient Discharge
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Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm.

Anesthesia and analgesia May 1, 2020
BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) <65 mm Hg lasting at least 5 consecutive minutes, are among the most critical events in the intensive care unit (ICU). They are known to be associated...
Humans Machine Learning Algorithms Male Middle Aged Cohort Studies Predictive Value of Tests Intensive Care Units Female Hospitalization Aged Acute Disease Hypotension
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Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.

Anesthesiology May 1, 2020
BACKGROUND: Although prediction of hospital readmissions has been studied in medical patients, it has received relatively little attention in surgical patient populations. Published predictors require information only available at the moment of disch...
Patient Readmission Machine Learning Hospitalization Humans Emergency Service, Hospital Patient Discharge
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Commentary: Laser Ablation of Abnormal Neurological Tissue Using Robotic Neuroblate System (LAANTERN): Procedural Safety and Hospitalization.

Neurosurgery Apr 1, 2020
Laser Therapy Hospitalization Robotics Robotic Surgical Procedures Humans
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Temporal convolutional networks allow early prediction of events in critical care.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2020
OBJECTIVE: Clinical interventions and death in the intensive care unit (ICU) depend on complex patterns in patients' longitudinal data. We aim to anticipate these events earlier and more consistently so that staff can consider preemptive action.
Aged, 80 and over Male Middle Aged Hospital Mortality Logistic Models Critical Care Intensive Care Units Female Hospitalization Aged Machine Learning Computer Simulation Prognosis Humans Neural Networks, Computer
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Using applied machine learning to predict healthcare utilization based on socioeconomic determinants of care.

The American journal of managed care Jan 1, 2020
OBJECTIVES: To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data.
Social Determinants of Health Humans Risk Georgia Young Adult Child Adult Socioeconomic Factors Male Patient Acceptance of Health Care Decision Trees Ohio Infant Middle Aged Emergency Service, Hospital Alabama Adolescent Child, Preschool Machine Learning Female Hospitalization Aged
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A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis Jan 1, 2020
Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30% of severely injured patients who are admitted to emergency departments (EDs). Given that conventio...
Humans Risk Assessment Emergencies Predictive Value of Tests International Normalized Ratio Blood Coagulation Disorders Wounds and Injuries Hospitalization Adult Male Middle Aged Machine Learning Algorithms Female
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Assessing clinical heterogeneity in sepsis through treatment patterns and machine learning.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns contained within granular data of electronic health records.
Aged, 80 and over Electronic Health Records Patient Acuity Middle Aged Female Quality of Health Care Adult Sepsis Humans Hospitalization Male Hospital Mortality Aged Anti-Bacterial Agents Unsupervised Machine Learning Retrospective Studies
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Comment on "Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission".

Annals of surgery Dec 1, 2019
Machine Learning Intensive Care Units Hospitalization Humans
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