Intensivists

Optimal adaptive control of drug dosing using integral reinforcement learning.

In this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, we use the common anesthetic drug propofol used in intensive care units (ICUs). The proposed online integral reinforcement learning (IRL) algorithm is designed to provide optimal ...

Potential EEG biomarkers of sedation doses in intensive care patients unveiled by using a machine learning approach.

OBJECTIVE: Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. Hence, we aim to evaluate the existence of changes of diverse EEG-derived measures in deeply-sedated (RASS-Richmond agitation-sedation scale  -4 and  ...

Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages.

High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative prognosis for this cohort can lead to better treatment plann...

Deep Learning Based Attenuation Correction of PET/MRI in Pediatric Brain Tumor Patients: Evaluation in a Clinical Setting.

Positron emission tomography (PET) imaging is a useful tool for assisting in correct differentiation of tumor progression from reactive changes. O-(2...

Prediction of sepsis patients using machine learning approach: A meta-analysis.

STUDY OBJECTIVE: Sepsis is a common and major health crisis in hospitals globally. An innovative and feasible tool for predicting sepsis remains elusi...

Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neu...

Serum Procalcitonin and Presepsin Levels in Patients with Generalized Pustular Psoriasis.

Patients with generalized pustular psoriasis (GPP) often present with symptoms that must be differentiated from sepsis. Procalcitonin (PCT) and presep...

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models...

Association Between Early Intravenous Fluids Provided by Paramedics and Subsequent In-Hospital Mortality Among Patients With Sepsis.

IMPORTANCE: Early administration of intravenous fluids is recommended for all patients with sepsis, but the association of this treatment with mortali...

Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data.

IMPORTANCE: Accurate prediction of outcomes among patients in intensive care units (ICUs) is important for clinical research and monitoring care quali...

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, t...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objectiv...

An Interpretable ICU Mortality Prediction Model Based on Logistic Regression and Recurrent Neural Networks with LSTM units.

Most existing studies used logistic regression to establish scoring systems to predict intensive care unit (ICU) mortality. Machine learning-based app...

Comparison of machine learning models for the prediction of mortality of patients with unplanned extubation in intensive care units.

Unplanned extubation (UE) can be associated with fatal outcome; however, an accurate model for predicting the mortality of UE patients in intensive ca...

Vitamin D in the ICU: More sun for critically ill adult patients?

Critical illness in patients is characterized by systemic inflammation and oxidative stress. Vitamin D has a myriad of biological functions relevant t...

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 prognosticati...

Analysis of platelet-activating factors in severe sepsis by flow cytometry and its correlation with clinical sepsis scoring system: A pilot study.

BACKGROUND: Sepsis is a major global healthcare concern. Platelets and leucocytes play a key role in sepsis. Whole blood flow cytometry (FCM) is a pow...

Using machine learning to guide targeted and locally-tailored empiric antibiotic prescribing in a children's hospital in Cambodia.

: Early and appropriate empiric antibiotic treatment of patients suspected of having sepsis is associated with reduced mortality. The increasing preva...

Changes of Early Sepsis Biomarker Presepsin Level during Hemodialysis: Influence of β-Microglobulin Clearance of Dialysis Membrane: A Preliminary Study.

BACKGROUND: Although presepsin (P-SEP) is an early sepsis biomarker, sepsis is often suspected after starting hemodialysis (HD). To enhance the utilit...

Critically Ill Recipients of Weight-Based Fluconazole Meeting Drug-Induced Liver Injury Network Criteria.

Fluconazole-associated liver injury is estimated to occur in <10% of patients; however, effect of weight-based fluconazole dosing on liver injury is ...