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Hospital-Based-Medicine Subcategories: Hospitalists Infection Control Intensivists Nursing Risk Management Surveillance

Showing 883-903 of 4,973 articles

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

Digital reconstruction of neuronal structures is very important to neuroscience research. Many exist...

Feb 2021 33055023

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus,...

Feb 2021 33524039

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is ...

Jan 2021 33514699

A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation.

Deep learning models are increasingly studied in the field of critical care. However, due to the lac...

Jan 2021 33936437

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.

The potential of Reinforcement Learning (RL) has been demonstrated through successful applications t...

Jan 2021 33936452

Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms.

The efficacy of early fluid treatment in patients with sepsis is unclear and may contribute to serio...

Jan 2021 33936436

[Artificial intelligence in neurocritical care].

Artificial intelligence (AI) has been introduced into medicine and an AI-assisted medicine will be t...

Jan 2021 33491152

Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma.

OBJECTIVE: To develop machine learning (ML) models capable of predicting ICU admission and extended ...

Jan 2021 33475772

Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome.

OBJECTIVE: To study if limited frontotemporal electroencephalogram (EEG) can guide sedation changes ...

Jan 2021 33567379

A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

INTRODUCTION: Patients with sepsis who present to an emergency department (ED) have highly variable ...

Jan 2021 33465096

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of Dece...

Jan 2021 33550068

Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

BACKGROUND: Passive leg raising (PLR) predicts fluid responsiveness in critical illness, although re...

Jan 2021 33461735

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm.

STUDY OBJECTIVE: Machine-learning algorithms allow improved prediction of sepsis syndromes in the em...

Jan 2021 33455840

Development of a machine learning model for predicting pediatric mortality in the early stages of intensive care unit admission.

The aim of this study was to develop a predictive model of pediatric mortality in the early stages o...

Jan 2021 33441845

Deep Multi-Magnification Networks for multi-class breast cancer image segmentation.

Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the...

Jan 2021 33485058

Interpreting a recurrent neural network's predictions of ICU mortality risk.

Deep learning has demonstrated success in many applications; however, their use in healthcare has be...

Jan 2021 33422663

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models.

There is increasing interest in the use of mechanism-based multi-scale computational models (such as...

Dec 2020 34744189

Five novel clinical phenotypes for critically ill patients with mechanical ventilation in intensive care units: a retrospective and multi database study.

BACKGROUND: Although protective mechanical ventilation (MV) has been used in a variety of applicatio...

Dec 2020 33302940

Hospital-Based Medicine

Browse Categories

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation.

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.

Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms.

[Artificial intelligence in neurocritical care].

Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma.

Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome.

A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.

Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm.

Development of a machine learning model for predicting pediatric mortality in the early stages of intensive care unit admission.

Deep Multi-Magnification Networks for multi-class breast cancer image segmentation.

Interpreting a recurrent neural network's predictions of ICU mortality risk.

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models.

Five novel clinical phenotypes for critically ill patients with mechanical ventilation in intensive care units: a retrospective and multi database study.

Moderate to severe leukocytosis with vasopressor use is associated with increased mortality in trauma patients.

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost.

Transfer learning with chest X-rays for ER patient classification.

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