AIMC Topic: Hospital Mortality

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Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network.

Respiratory research Sep 23, 2022
BACKGROUND: Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk str...
Machine Learning Retrospective Studies Female Humans Hospitals Hospital Mortality Pneumonia Aged Male
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Machine learning to predict adverse outcomes after cardiac surgery: A systematic review and meta-analysis.

Journal of cardiac surgery Aug 24, 2022
BACKGROUND: Machine learning (ML) models are promising tools for predicting adverse postoperative outcomes in cardiac surgery, yet have not translated to routine clinical use. We conducted a systematic review and meta-analysis to assess the predictiv...
Cardiac Surgical Procedures Humans Logistic Models Machine Learning Hospital Mortality Bayes Theorem
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Phenotypes of sickle cell intensive care admissions: an unsupervised machine learning approach in a single-center retrospective cohort.

Annals of hematology Jul 15, 2022
Sickle cell disease (SCD) is associated with multiple known complications and increased mortality. This study aims to further understand the profile of intensive care unit (ICU) admissions of SCD patients. In this single-center retrospective cohort (...
Humans Intensive Care Units Female Male Phenotype Retrospective Studies Unsupervised Machine Learning Critical Care Brazil Anemia, Sickle Cell Hospital Mortality
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Which model is superior in predicting ICU survival: artificial intelligence versus conventional approaches.

BMC medical informatics and decision making Jun 26, 2022
BACKGROUND: A disease severity classification system is widely used to predict the survival of patients admitted to the intensive care unit with different diagnoses. In the present study, conventional severity classification systems were compared wit...
ROC Curve APACHE Intensive Care Units Hospital Mortality Humans Prognosis Retrospective Studies Artificial Intelligence
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Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies May 5, 2022
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.
ROC Curve Intensive Care Units Child Hospital Mortality Machine Learning Retrospective Studies Humans
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Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset.

Scientific reports May 3, 2022
The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fai...
Deep Learning Hospital Mortality Benchmarking Critical Care Humans Forecasting
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Cardiac auscultation predicts mortality in elderly patients admitted for COVID-19.

Hospital practice (1995) Apr 29, 2022
INTRODUCTION: COVID-19 has had a great impact on the elderly population. All admitted patients underwent cardiac auscultation at the Emergency Department. However, to our knowledge, there is no literature that explains the implications of cardiac aus...
Heart Auscultation Aged Female Hospital Mortality Aged, 80 and over Male Humans Hospitalization Arrhythmias, Cardiac COVID-19
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Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network.

BMC anesthesiology Apr 23, 2022
BACKGROUND: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), make...
Artificial Intelligence Humans Intensive Care Units Hospital Mortality Hospitalization ROC Curve
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Implementation of a machine learning application in preoperative risk assessment for hip repair surgery.

BMC anesthesiology Apr 23, 2022
BACKGROUND: This study aims to develop a machine learning-based application in a real-world medical domain to assist anesthesiologists in assessing the risk of complications in patients after a hip surgery.
Area Under Curve Risk Assessment Hospital Mortality ROC Curve Intensive Care Units Adult Humans Machine Learning Retrospective Studies
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Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.

Journal of medical Internet research Apr 13, 2022
BACKGROUND: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algor...
Humans Adult Sepsis Machine Learning Logistic Models Hospital Mortality ROC Curve
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