BACKGROUND: Beatriz Nistal-Nuño designed a machine learning system type of ensemble learning for patients undergoing cardiac surgery and intensive care unit cardiology patients, based on sequences of cardiovascular physiological measurements and othe...
BACKGROUND: The purpose of this study was to develop and validate a mortality risk algorithm for pediatric surgery patients treated at KidsOR sites in 14 low- and middle-income countries.
AIMS: This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).
CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
39284602
BACKGROUND: The implementation and clinical impact of machine learning-based early warning systems for patient deterioration in hospitals have not been well described. We sought to describe the implementation and evaluation of a multifaceted, real-ti...
BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop ...
International journal of medical informatics
39546949
BACKGROUND: The assessment of clinical outcome quality, particularly in surgery, is crucial for healthcare improvement. Traditional cross-sectional analyses often fall short in timely and systematic identification of clinical quality issues. This stu...
BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome following pediatric decompressive craniectomy (DC) performed after traumatic brain injury (TBI). The aim of this study was to develop a random forest ...
Anaesthesia, critical care & pain medicine
39366654
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
39379230
BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for i...
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...