AIMC Topic: Hospitalization
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Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model.
BMJ open
Jul 9, 2019
INTRODUCTION: Asthma is a long-term condition with rapid onset worsening of symptoms ('attacks') which can be unpredictable and may prove fatal. Models predicting asthma attacks require high sensitivity to minimise mortality risk, and high specificit...
Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.
Acta psychiatrica Scandinavica
Jul 6, 2019
OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others during inpatient treatment. The objective of this study was to investigate whether incident MR occurring in the first 3 days following admission could ...
Prediction of emergency department patient disposition based on natural language processing of triage notes.
International journal of medical informatics
Jun 13, 2019
BACKGROUND: Nursing triage documentation is the first free-form text data created at the start of an emergency department (ED) visit. These 1-3 unstructured sentences reflect the clinical impression of an experienced nurse and are key in gauging a pa...
FriWalk robotic walker: usability, acceptance and UX evaluation after a pilot study in a real environment.
Disability and rehabilitation. Assistive technology
Jun 7, 2019
: Scientific evidence supports that prevention strategies like multicomponent physical exercise help avoiding functional decline, falls and frailty. The robotic walker FriWalk, developed within the ACANTO project, supports the execution of controlled...
Machine learning approaches for risk assessment of peripherally inserted Central catheter-related vein thrombosis in hospitalized patients with cancer.
International journal of medical informatics
Jun 7, 2019
OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis based on machine learning (ML) techniques considering genotype.
Estimating the association between antibiotic exposure and colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria using machine learning methods: a multicentre, prospective cohort study.
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
May 23, 2019
OBJECTIVES: The aim of the study was to measure the impact of antibiotic exposure on the acquisition of colonization with extended-spectrum β-lactamase-producing Gram-negative bacteria (ESBL-GNB) accounting for individual- and group-level confounding...
Evidential MACE prediction of acute coronary syndrome using electronic health records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with acute coronary syndrome (ACS) during their hospitalizations. Existing prediction models have limita...
Smooth Bayesian network model for the prediction of future high-cost patients with COPD.
International journal of medical informatics
Apr 4, 2019
INTRODUCTION: The clinical course of chronic obstructive pulmonary disease (COPD) is marked by acute exacerbation events that increase hospitalization rates and healthcare spending. The early identification of future high-cost patients with COPD may ...
Feature-weighted survival learning machine for COPD failure prediction.
Artificial intelligence in medicine
Mar 28, 2019
Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting su...
Patient Readmission
Survival Analysis
Hospitalization
Retrospective Studies
Canada
Humans
Male
Aged
Proportional Hazards Models
Electronic Health Records
Age Factors
Machine Learning
Aged, 80 and over
Middle Aged
Female
Predictive Value of Tests
Biomarkers
Pulmonary Disease, Chronic Obstructive
Severity of Illness Index
Prognosis
Risk Factors
Sex Factors
Time Factors
ROC Curve
Assessment of Machine Learning vs Standard Prediction Rules for Predicting Hospital Readmissions.
JAMA network open
Mar 1, 2019
IMPORTANCE: Hospital readmissions are associated with patient harm and expense. Ways to prevent hospital readmissions have focused on identifying patients at greatest risk using prediction scores.
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