AIMC Topic: Hospital Mortality

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Treatment of individual predictors with neural network algorithms improves Global Registry of Acute Coronary Events score discrimination.

Archivos de cardiologia de Mexico Jan 1, 2021
OBJECTIVE: The aim of this study was to develop, train, and test different neural network (NN) algorithm-based models to improve the Global Registry of Acute Coronary Events (GRACE) score performance to predict in-hospital mortality after an acute co...
Prognosis Female Aged Male Middle Aged Humans Neural Networks, Computer Algorithms Databases, Factual Hospital Mortality Registries Acute Coronary Syndrome
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Design of 1-year mortality forecast at hospital admission: A machine learning approach.

Health informatics journal Jan 1, 2021
Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-y...
Retrospective Studies Hospitalization Quality of Life Hospitals Hospital Mortality Humans Machine Learning
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Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
OBJECTIVE: In applying machine learning (ML) to electronic health record (EHR) data, many decisions must be made before any ML is applied; such preprocessing requires substantial effort and can be labor-intensive. As the role of ML in health care gro...
Intensive Care Units ROC Curve Electronic Health Records Data Management Humans Respiratory Insufficiency Machine Learning Risk Assessment Data Mining Databases, Factual Hospital Mortality Shock
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Dr. Agent: Clinical predictive model via mimicked second opinions.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Prediction of disease phenotypes and their outcomes is a difficult task. In practice, patients routinely seek second opinions from multiple clinical experts for complex disease diagnosis. Our objective is to mimic such a practice of seekin...
Humans Neural Networks, Computer Computer Simulation Prognosis Logistic Models Disease Progression Referral and Consultation Deep Learning Length of Stay Hospital Mortality
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Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care.

The Journal of pediatrics Jun 1, 2020
Intensive Care Units, Pediatric Blood Transfusion Critical Care Hemorrhage Anesthesia Postoperative Complications Monitoring, Intraoperative Ultrasonography Hospital Mortality Perioperative Care Patient Admission Intraoperative Complications Heart Arrest Airway Management Humans Artificial Intelligence Machine Learning Algorithms Biomedical Research Risk Assessment
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Deep learning-based quantitative visualization and measurement of extraperitoneal hematoma volumes in patients with pelvic fractures: Potential role in personalized forecasting and decision support.

The journal of trauma and acute care surgery Mar 1, 2020
INTRODUCTION: Admission computed tomography (CT) is a widely used diagnostic tool for patients with pelvic fractures. In this pilot study, we hypothesized that pelvic hematoma volumes derived using a rapid automated deep learning-based quantitative v...
Humans Algorithms Pelvic Bones Fractures, Bone Blood Transfusion Embolization, Therapeutic Middle Aged Hematoma Retrospective Studies Endotamponade Deep Learning Female Pilot Projects Adult Hospital Mortality Male Decision Support Systems, Clinical
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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.
Hospital Mortality Logistic Models Critical Care Hospitalization Aged Humans Aged, 80 and over Neural Networks, Computer Male Machine Learning Middle Aged Computer Simulation Prognosis Intensive Care Units Female
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A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Dec 1, 2019
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...
Infant Severity of Illness Index Adolescent Humans Prospective Studies Rwanda Child Machine Learning Prognosis Developing Countries Child, Preschool Hospital Mortality Female Child Mortality Age Factors Male Sex Factors Triage Infections Vital Signs
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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.
Male Middle Aged Sepsis Hospital Mortality Unsupervised Machine Learning Patient Acuity Quality of Health Care Female Humans Hospitalization Anti-Bacterial Agents Aged Retrospective Studies Aged, 80 and over Electronic Health Records Adult
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Machine Learning Prediction Models for In-Hospital Mortality After Transcatheter Aortic Valve Replacement.

JACC. Cardiovascular interventions Jul 22, 2019
OBJECTIVES: This study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.
Clinical Decision-Making Male Humans Treatment Outcome Risk Assessment Female Machine Learning Predictive Value of Tests Risk Factors Hospital Mortality Decision Support Techniques Transcatheter Aortic Valve Replacement Aged United States Databases, Factual Aged, 80 and over
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