Intensivists

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (ICU) existing automated alarm systems typically rely on simple thresholding that result in frequent false positives. Recurrent false positive alerts c...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. However, patients with sepsis continue to be at risk of death after hospital discharge.

The Benefit of Fentanyl in Effective Sedation and Quality of Upper Endoscopy: A Double-Blinded Randomized Trial of Fentanyl Added to Midazolam Versus Midazolam Alone for Sedation.

AIMS: Our goals were to compare the effect of adding fentanyl to midazolam in a double-blinded, randomized, placebo-controlled trial and determine if ...

Improved multi-view privileged support vector machine.

Multi-view learning (MVL) concentrates on the problem of learning from the data represented by multiple distinct feature sets. The consensus and compl...

Minimally Invasive Surgical Approach for Posterior Tracheopexy to Treat Severe Tracheomalacia: Lessons Learned from Initial Case Series.

Posterior tracheopexy directly addresses membranous tracheal intrusion in severe tracheomalacia (TM). We have previously reported our experience of p...

2.5-Dimensional Parylene C micropore array with a large area and a high porosity for high-throughput particle and cell separation.

Large-area micropore arrays with a high porosity are in high demand because of their promising potential in liquid biopsy with a large volume of clini...

Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks.

Environmental sustainability research is dependent on accurate land cover information. Even with the increased number of satellite systems and sensors...

Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most...

Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform.

Sputum sounds are biological signals used to evaluate the condition of sputum deposition in a respiratory system. To improve the efficiency of intensi...

Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification.

This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequence...

Machine Learning for Outcome Prediction in Electroencephalograph (EEG)-Monitored Children in the Intensive Care Unit.

The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous elec...

Ultra-protective mechanical ventilation without extra-corporeal carbon dioxide removal for acute respiratory distress syndrome.

BACKGROUND: Tidal hyperinflation can still occur with mechanical ventilation using low tidal volume (LVT) (6 mL/kg predicted body weight (PBW)) in acu...

Replicating human expertise of mechanical ventilation waveform analysis in detecting patient-ventilator cycling asynchrony using machine learning.

BACKGROUND: - Acute respiratory failure is one of the most common problems encountered in intensive care units (ICU) and mechanical ventilation is the...

Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationshi...

Healthcare-associated ventriculitis and meningitis in a neuro-ICU: Incidence and risk factors selected by machine learning approach.

PURPOSE: To define the incidence of healthcare-associated ventriculitis and meningitis (HAVM) in the neuro-ICU and to identify HAVM risk factors using...

Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.

BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essenti...

Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome.

When training a machine learning algorithm for a supervised-learning task in some clinical applications, uncertainty in the correct labels of some pat...

Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier.

Electronic health records (EHRs) contain critical information useful for clinical studies. Early assessment of patients' mortality in intensive care u...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The ...

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.

OBJECTIVES: We validate a machine learning-based sepsis-prediction algorithm () for the detection and prediction of three sepsis-related gold standard...