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Intensive Care Units

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COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data.

European radiology
OBJECTIVES: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU).

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Scientific reports
Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time periods for ...

Early heart rate variability evaluation enables to predict ICU patients' outcome.

Scientific reports
Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activity, and a relation between HRV and outcome has been proposed in various types of patients. We attempted to evaluate the best determinants of such var...

External Validation of a Laboratory Prediction Algorithm for the Reduction of Unnecessary Labs in the Critical Care Setting.

The American journal of medicine
BACKGROUND: Unnecessary laboratory tests contribute to iatrogenic harm and are a major source of waste in the health care system. We previously developed a machine learning algorithm to help clinicians identify unnecessary laboratory tests, but it ha...

Developing machine learning models for prediction of mortality in the medical intensive care unit.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alert of patient deterioration is essential for prompt medical intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been used for the development of most conventional severity-of-illness scori...

Machine Learning Approaches-Driven for Mortality Prediction for Patients Undergoing Craniotomy in ICU.

Brain injury
OBJECTIVES: We aimed to predict the mortality of patients with craniotomy in ICU by using predictive models to extract the high-risk factors leading to the death of patients from a retrospective a study.

Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.

International wound journal
The study aimed to establish a machine learning-based scoring nomogram for early recognition of likely pressure injuries in an intensive care unit (ICU) using large-scale clinical data. A retrospective cohort study design was employed to develop and ...

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks.

Journal of cellular and molecular medicine
There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death,...

Improving the In-Hospital Mortality Prediction of Diabetes ICU Patients Using a Process Mining/Deep Learning Architecture.

IEEE journal of biomedical and health informatics
Diabetes intensive care unit (ICU) patients are at increased risk of complications leading to in-hospital mortality. Assessing the likelihood of death is a challenging and time-consuming task due to a large number of influencing factors. Healthcare p...