AIMC Topic: Hospital Mortality

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Health system-scale language models are all-purpose prediction engines.

Nature Jun 7, 2023
Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by forecasting clinical and operational events. Existing structured data-based clinical predictive models ...
Comorbidity Length of Stay Hospital Mortality Clinical Decision-Making Point-of-Care Systems Patient Readmission Clinical Trials as Topic Insurance Coverage Natural Language Processing Area Under Curve Physicians Electronic Health Records Humans
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The implementation of a real time early warning system using machine learning in an Australian hospital to improve patient outcomes.

Resuscitation May 5, 2023
BACKGROUND: Early Warning Scores (EWS) monitor inpatient deterioration predominantly using vital signs. We evaluated inpatient outcomes after implementing an Artificial Intelligence (AI) based intervention in our local EWS.
Machine Learning Female Hospitalization Humans Artificial Intelligence Hospitals Hospital Mortality Australia Aged Male
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Enabling personalized perioperative risk prediction by using a machine-learning model based on preoperative data.

Scientific reports May 2, 2023
Preoperative risk assessment is essential for shared decision-making and adequate perioperative care. Common scores provide limited predictive quality and lack personalized information. The aim of this study was to create an interpretable machine-lea...
Risk Assessment Retrospective Studies Hospital Mortality Risk Factors Humans Machine Learning
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Comparison of correctly and incorrectly classified patients for in-hospital mortality prediction in the intensive care unit.

BMC medical research methodology Apr 24, 2023
BACKGROUND: The use of machine learning is becoming increasingly popular in many disciplines, but there is still an implementation gap of machine learning models in clinical settings. Lack of trust in models is one of the issues that need to be addre...
APACHE Algorithms Intensive Care Units Humans Hospital Mortality Machine Learning
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Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms.

BMC medical research methodology Apr 22, 2023
BACKGROUND: Trauma is one of the most critical public health issues worldwide, leading to death and disability and influencing all age groups. Therefore, there is great interest in models for predicting mortality in trauma patients admitted to the IC...
Hospital Mortality Bayes Theorem Humans Algorithms Retrospective Studies Machine Learning
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A Multidatabase ExTRaction PipEline (METRE) for facile cross validation in critical care research.

Journal of biomedical informatics Apr 5, 2023
Transforming raw EHR data into machine learning model-ready inputs requires considerable effort. One widely used EHR database is Medical Information Mart for Intensive Care (MIMIC). Prior work on MIMIC-III cannot query the updated and improved MIMIC-...
Databases, Factual Intensive Care Units Area Under Curve Critical Care Hospital Mortality Humans Machine Learning
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Predicting heart failure in-hospital mortality by integrating longitudinal and category data in electronic health records.

Medical & biological engineering & computing Mar 24, 2023
Heart failure is a life-threatening syndrome that is diagnosed in 3.6 million people worldwide each year. We propose a deep fusion learning model (DFL-IMP) that uses time series and category data from electronic health records to predict in-hospital ...
Machine Learning Electronic Health Records Hospital Mortality Heart Failure Hospitalization Humans
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Clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making.

The Journal of thoracic and cardiovascular surgery Feb 2, 2023
OBJECTIVES: The aim of this study using decision curve analysis (DCA) was to evaluate the clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making compared with the European System for Cardiac Operative Risk ...
Cardiac Surgical Procedures ROC Curve Decision Making Humans Risk Assessment Deep Learning Artificial Intelligence Hospital Mortality Retrospective Studies
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Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea.

Journal of medical Internet research Dec 13, 2022
BACKGROUND: Physical trauma-related mortality places a heavy burden on society. Estimating the mortality risk in physical trauma patients is crucial to enhance treatment efficiency and reduce this burden. The most popular and accurate model is the In...
Injury Severity Score Artificial Intelligence Trauma Severity Indices Republic of Korea Retrospective Studies Humans Hospital Mortality
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Development, validation, and feature extraction of a deep learning model predicting in-hospital mortality using Japan's largest national ICU database: a validation framework for transparent clinical Artificial Intelligence (cAI) development.

Anaesthesia, critical care & pain medicine Oct 24, 2022
OBJECTIVE: While clinical Artificial Intelligence (cAI) mortality prediction models and relevant studies have increased, limitations including the lack of external validation studies and inadequate model calibration leading to decreased overall accur...
Hospital Mortality Japan Intensive Care Units Humans Deep Learning Artificial Intelligence
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