Intensivists

Advances in the rehabilitation of intensive care unit acquired weakness: A case report on the promising use of robotics and virtual reality coupled to physiotherapy.

INTRODUCTION: Traditional physiotherapy is currently the best approach to manage patients with inten...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction...

Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.

Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to...

Practical Machine Learning-Based Sepsis Prediction.

Sepsis is a life-threatening clinical syndrome and one of the most expensive conditions treated in h...

Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal.

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a ...

Deep transfer learning for video-based detection of newborn presence in incubator.

Preterm newborns are prone to late-onset sepsis, leading to a high risk of mortality. Video-based an...

Extracting Membrane Borders in IVUS Images Using a Multi-Scale Feature Aggregated U-Net.

Automatic extraction of the lumen-intima border (LIB) and the media-adventitia border (MAB) in intra...

Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often ti...

MDL-IWS: Multi-view Deep Learning with Iterative Watershed for Pulmonary Fissure Segmentation.

Pulmonary fissure segmentation is important for localization of lung lesions which include nodules a...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction...

Blood Lactate Concentration Prediction in Critical Care.

Blood lactate concentration is a reliable risk indicator of deterioration in critical care requiring...

Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images-a Comparative Insight.

Automatic multi-classification of breast cancer histopathological images has remained one of the top...

Comparative outcomes of robot-assisted minimally invasive versus open esophagectomy in patients with esophageal squamous cell carcinoma: a propensity score-weighted analysis.

Robots are increasingly used in minimally invasive surgery. We evaluated the clinical benefits of ro...

Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

BACKGROUND: Shape is a critical element of the visual appeal of strawberry fruit and is influenced b...

Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm.

BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) ...

On classifying sepsis heterogeneity in the ICU: insight using machine learning.

OBJECTIVES: Current machine learning models aiming to predict sepsis from electronic health records ...

Temporal convolutional networks allow early prediction of events in critical care.

OBJECTIVE: Clinical interventions and death in the intensive care unit (ICU) depend on complex patte...

Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack co...

[Prognostic model of small sample critical diseases based on transfer learning].

Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic mo...

A deep neural network based hierarchical multi-label classification method.

With the accumulation of data generated by biological experimental instruments, using hierarchical m...

Too Many Definitions of Sepsis: Can Machine Learning Leverage the Electronic Health Record to Increase Accuracy and Bring Consensus?