Hospitalists

Optimal intensive care outcome prediction over time using machine learning.

BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognostication in ICU has so far been limited to data from admission or the first 24 hours. Most ICU admissions last longer than this, decisions are made throughout an admission, and some admissions are explicitly intended as time-limited prognostic trials. Desp...

Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

River water temperature is a key control of many physical and bio-chemical processes in river systems, which theoretically depends on multiple factors. Here, four different machine learning models, including multilayer perceptron neural network models (MLPNN), adaptive neuro-fuzzy inference systems (ANFIS) with fuzzy c-mean clustering algorithm (ANFIS_FC), ANFIS with grid partition method (ANFIS_G...

Using an artificial neural network to predict traumatic brain injury.

In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients wh...

Low vitamin D at ICU admission is associated with cancer, infections, acute respiratory insufficiency, and liver failure.

OBJECTIVES: Vitamin D deficiency may be associated with comorbidities and poor prognosis. However, this association in patients in the intensive care ...

Modeling daily suspended sediment load using improved support vector machine model and genetic algorithm.

Prediction of sediment volume and sediment load is always one of the important issues for decision-makers of watershed basins. The present study inves...

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances.

The importance of incorporating Natural Language Processing (NLP) methods in clinical informatics research has been increasingly recognized over the p...

Utilizing soft constraints to enhance medical relation extraction from the history of present illness in electronic medical records.

Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous res...

Comparison of MetaMap and cTAKES for entity extraction in clinical notes.

BACKGROUND: Clinical notes such as discharge summaries have a semi- or unstructured format. These documents contain information about diseases, treatm...

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 ...

Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reas...

Decontamination of collards ( var. L.) using electrolyzed water and corona discharge plasma jet.

Acidic electrolyzed water (AEW) was used for collards sanitization. In the AEW (pH of 3.6; 230 mg/L chlorine) generator, the rates of brine inflow and...

Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. ...

Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients.

To assess functional status and robot-based kinematic measures four years after subacute robot-assisted rehabilitation in hemiparesis. Twenty-two pa...

Using Machine Learning to Improve the Prediction of Functional Outcome in Ischemic Stroke Patients.

Ischemic stroke is a leading cause of disability and death worldwide among adults. The individual prognosis after stroke is extremely dependent on tre...

Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.

Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in thes...

Epileptic seizure detection using DWT-based approximate entropy, Shannon entropy and support vector machine: a case study.

In this work, we have used a time-frequency domain analysis method called discrete wavelet transform (DWT) technique. This method stand out compared t...

Can a standardised Ventilation Mechanical Test for quantitative intraoperative air leak grading reduce the length of hospital stay after video-assisted thoracoscopic surgery lobectomy?

We standardised a Ventilation Mechanical Test (VMT) after video-assisted thoracoscopic surgery (VATS) lobectomy that classifies intraoperative alveola...

Determination of nitrite in water samples using atmospheric pressure glow discharge microplasma emission and chemical vapor generation of NO species.

In this work, a low-power (<25 W), portable direct current (dc) atmospheric pressure glow discharge microplasma (4 mm × 10  mm) molecular emission spe...

Developing a Machine Learning System for Identification of Severe Hand, Foot, and Mouth Disease from Electronic Medical Record Data.

Children of severe hand, foot, and mouth disease (HFMD) often present with same clinical features as those of mild HFMD during the early stage, yet la...

Endothelial markers in high altitude induced systemic hypertension (HASH) at moderate high altitude.

BACKGROUND: Chronic intermittent hypoxia is known to induce systemic arterial hypertension whereas chronic hypoxia causes pulmonary arterial hypertens...