Sepsis

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides.

BACKGROUND: Current methods in machine learning provide approaches for solving challenging, multiple...

Martial Arts Routine Training Method Based on Artificial Intelligence and Big Data of Lactate Measurement.

As a traditional Chinese sport, competitive martial arts routines have a long history. The competiti...

Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid.

PROBLEM: Preterm birth (PTB) is a major cause of increased morbidity and mortality in newborns. The ...

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images.

Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients w...

A predictive framework in healthcare: Case study on cardiac arrest prediction.

Data-driven healthcare uses predictive analytics to enhance decision-making and personalized healthc...

Research on Enhanced Detection of Benzoic Acid Additives in Liquid Food Based on Terahertz Metamaterial Devices.

It is very important for human health to supervise the use of food additives, because excessive use ...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbid...

Can artificial intelligence and machine learning help us treat sepsis?

NIA-Network: Towards improving lung CT infection detection for COVID-19 diagnosis.

During pandemics (e.g., COVID-19) physicians have to focus on diagnosing and treating patients, whic...

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administ...

Computational medication regimen for Parkinson's disease using reinforcement learning.

Our objective is to derive a sequential decision-making rule on the combination of medications to mi...

Machine Learning-Based Prediction of Growth in Confirmed COVID-19 Infection Cases in 114 Countries Using Metrics of Nonpharmaceutical Interventions and Cultural Dimensions: Model Development and Validation.

BACKGROUND: National governments worldwide have implemented nonpharmaceutical interventions to contr...

Physiological machine learning models for prediction of sepsis in hospitalized adults: An integrative review.

BACKGROUND: Diagnosing sepsis remains challenging. Data compiled from continuous monitoring and elec...

A controlled human infection model of Streptococcus pyogenes pharyngitis (CHIVAS-M75): an observational, dose-finding study.

BACKGROUND: Streptococcus pyogenes is a leading cause of infection-related morbidity and mortality. ...

Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data.

BACKGROUND: Survival of liver transplant recipients beyond 1 year since transplantation is compromis...

Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.

This positioning paper aims to discuss current challenges and opportunities for artificial intellige...

Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review.

BACKGROUND AND OBJECTIVES: Sepsis is a life-threatening condition that is associated with increased ...

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is...

Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.

IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant...

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and ...

Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a compl...