AIMC Topic: Hospitalization

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A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

JAMA network open Nov 1, 2021
IMPORTANCE: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by t...
Humans Forecasting Prognosis Female Disease Progression Cohort Studies Natural Language Processing Heart Failure Delivery of Health Care, Integrated Hospitalization Aged Male Middle Aged
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A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization.

JAMA network open Oct 1, 2021
IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic.
Humans Machine Learning COVID-19 Algorithms Clinical Decision Rules Benchmarking COVID-19 Testing Crowdsourcing Washington Aged Aged, 80 and over Young Adult Adult Prognosis Male Child, Preschool Female Middle Aged Child Infant, Newborn Infant ROC Curve Hospitalization Severity of Illness Index Models, Statistical Adolescent Area Under Curve
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Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering.

Medical sciences (Basel, Switzerland) Sep 24, 2021
BACKGROUND: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters.
Aged Aged, 80 and over Adult Male Humans Middle Aged Machine Learning Bicarbonates Acute Kidney Injury Female Hospitalization Hospital Mortality Consensus Cluster Analysis Chlorides
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Estimation of Baseline Serum Creatinine with Machine Learning.

American journal of nephrology Sep 20, 2021
INTRODUCTION: Comparing current to baseline serum creatinine is important in detecting acute kidney injury. In this study, we report a regression-based machine learning model to predict baseline serum creatinine.
Aged Humans Aged, 80 and over Machine Learning Middle Aged Adult Female Cohort Studies Male Hospitalization Creatinine
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Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran.

Scientific reports Aug 20, 2021
This study was aimed to investigate the air pollutants impact on heart patient's hospital admission rates in Yazd for the first time. Modeling was done by time series, multivariate linear regression, and artificial neural network (ANN). During 5 year...
Linear Models Humans Multivariate Analysis Neural Networks, Computer Patient Admission Infant Geography Young Adult Adolescent Female Adult Male Time Factors Child Cardiovascular Diseases Infant, Newborn Child, Preschool Air Pollutants Hospitalization Middle Aged Air Pollution Aged Seasons Iran
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Implementing an Individual-Centric Discharge Process across Singapore Public Hospitals.

International journal of environmental research and public health Aug 17, 2021
Singapore is one of the first known countries to implement an individual-centric discharge process across all public hospitals to manage frequent admissions-a perennial challenge for public healthcare, especially in an aging population. Specifically,...
Artificial Intelligence Hospitalization Aged Length of Stay Singapore Patient Discharge Hospitals, Public Humans
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Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors.

Scientific reports Aug 2, 2021
The COVID-19 pandemic continues to have a devastating impact on Brazil. Brazil's social, health and economic crises are aggravated by strong societal inequities and persisting political disarray. This complex scenario motivates careful study of the c...
Female SARS-CoV-2 Hospitalization Male Brazil Hospital Mortality Socioeconomic Factors Models, Biological Humans Machine Learning Pandemics COVID-19
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Automated ICD coding for primary diagnosis via clinically interpretable machine learning.

International journal of medical informatics Jul 27, 2021
BACKGROUND: Computer-assisted clinical coding (CAC) based on automated coding algorithms has been expected to improve the International Classification of Disease, tenth version (ICD-10) coding quality and productivity, whereas studies oriented to pri...
Machine Learning Humans Algorithms Hospitalization International Classification of Diseases Clinical Coding
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Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit.

Journal of biomedical informatics Jul 27, 2021
Interpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for L...
Hospitalization Deep Learning Humans Neural Networks, Computer Intensive Care Units Electronic Health Records
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Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jul 22, 2021
OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized...
Atrial Fibrillation Heart Rate Humans Embolic Stroke Predictive Value of Tests Artificial Intelligence Signal Processing, Computer-Assisted Male Female Registries Middle Aged Risk Factors Electrocardiography, Ambulatory Risk Assessment Hospitalization Time Factors Aged Action Potentials Aged, 80 and over
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