Critical Care

Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

5,092 articles

Subcategories: Sepsis

Showing 1765-1785 of 5,092 articles

Benchmarking machine learning models on multi-centre eICU critical care dataset.

Progress of machine learning in critical care has been difficult to track, in part due to absence of...

Jul 2020 32614874

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects.

This study presents a systematic review of artificial intelligence (AI) techniques used in the detec...

Jul 2020 32646771

Efficacy of enoxaparin in preventing coagulation during high-flux haemodialysis, expanded haemodialysis and haemodiafiltration.

BACKGROUND: Low-molecular-weight heparins (LMWHs) are easily dialysable with high-flow membranes; ho...

Jun 2020 33841857

A Knowledge-Based Machine Learning Approach to Gene Prioritisation in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis is a neurodegenerative disease of the upper and lower motor neurons re...

Jun 2020 32575372

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

BACKGROUND: The purpose of this review is to depict current research and impact of artificial intell...

Jun 2020 32596403

Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

BACKGROUND: Although dialysis patients are at a high risk of death, it is difficult for medical prac...

May 2020 32469924

Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.

Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including...

May 2020 32451808

Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.

BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many live...

May 2020 32454016

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. Ho...

May 2020 32437368

Applications of artificial intelligence and machine learning in respiratory medicine.

The past 5 years have seen an explosion of interest in the use of artificial intelligence (AI) and m...

May 2020 32409611

Deep Multi-Critic Network for accelerating Policy Learning in multi-agent environments.

Humans live among other humans, not in isolation. Therefore, the ability to learn and behave in mult...

May 2020 32446194

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneu...

May 2020 32416069

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-lea...

May 2020 32366838

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Benchmarking machine learning models on multi-centre eICU critical care dataset.

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects.

Efficacy of enoxaparin in preventing coagulation during high-flux haemodialysis, expanded haemodialysis and haemodiafiltration.

A Knowledge-Based Machine Learning Approach to Gene Prioritisation in Amyotrophic Lateral Sclerosis.

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.

Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

Applications of artificial intelligence and machine learning in respiratory medicine.

Deep Multi-Critic Network for accelerating Policy Learning in multi-agent environments.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Artificial intelligence to codify lung CT in Covid-19 patients.

Neurotransmitter networks in mouse prefrontal cortex are reconfigured by isoflurane anesthesia.

Exploration of critical care data by using unsupervised machine learning.

Bio-inspired multi-scale fusion.

Deep Multi-Scale Fusion Neural Network for Multi-Class Arrhythmia Detection.

Scoring pleurisy in slaughtered pigs using convolutional neural networks.

Implementation of an Artificial Intelligence Algorithm for sepsis detection.

Characterization of sodium removal to ultrafiltration volume in a peritoneal dialysis outpatient cohort.

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