Sepsis

The Use of Mobile Thermal Imaging and Deep Learning for Prediction of Surgical Site Infection.

The ability to detect surgical site infections (SSI) is a critical need for healthcare worldwide, but is especially important in low-income countries, where there is limited access to health facilities and trained clinical staff. In this paper, we present a new method of predicting SSI using a thermal image collected with a smart phone. Machine learning algorithms were developed using images colle...

Optimization of metronidazole SR buccal tablet for gingivitis using genetic algorithm.

Gingivitis is a condition that needs sustained concentration of antibiotic locally over extended period of time. The current study aimed to formulate and evaluate the sustained and localized release of metronidazole (MTZ) as mucoadhesive buccal tablet containing hydroxypropylmethyl cellulose (HPMC), Carbopol 940® (CP), carboxymethylcellulose (CMC) and ethyl cellulose (EC) as mucoadhesive polymers....

A Simulated Prospective Evaluation of a Deep Learning Model for Real-Time Prediction of Clinical Deterioration Among Ward Patients.

OBJECTIVES: The National Early Warning Score, Modified Early Warning Score, and quick Sepsis-related Organ Failure Assessment can predict clinical det...

Predictive Risk Models for Wound Infection-Related Hospitalization or ED Visits in Home Health Care Using Machine-Learning Algorithms.

OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds ...

Machine Learning and Artificial Intelligence for Surgical Decision Making.

The use of machine learning (ML) and artificial intelligence (AI) in medical research continues to grow as the amount and availability of clinical da...

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

OBJECTIVE: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the elec...

Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus.

BACKGROUND: A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and e...

Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults.

BACKGROUND: Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our pr...

Predicting the Need For Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model.

BACKGROUND: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose o...

Deep Learning-Based Nuclear Lobe Count Method for Differential Count of Neutrophils.

Differentiating neutrophils based on the count of nuclear lobulation is useful for diagnosing various hematological disorders, including megaloblastic...

Towards real-time diagnosis for pediatric sepsis using graph neural network and ensemble methods.

OBJECTIVE: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Time...

Predicting ventilator-associated pneumonia with machine learning.

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifyi...

Minimally Invasive Hernia Repair in Robot-assisted Radical Prostatectomy.

Inguinal hernia is a recognized complication of radical prostatectomy. Previous hernia repair, wound infection, midline incision, low BMI, and preexis...

Predicting Antibiotic Resistance in Hospitalized Patients by Applying Machine Learning to Electronic Medical Records.

BACKGROUND: Computerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning (ML) algor...

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis...

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2....

[An evidence-based analysis comparing two approaches of robot-assisted laparoscopic radical prostatectomy: the standard technique and Retzius-sparing technique].

To compare the postoperative outcomes and urinary continence recovery time between standard robotic-assisted laparoscopic radical prostatectomy (RARP...

High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status.

Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometr...

[A Case of Descending Colon and Rectal Cancer with Acute Myeloid Leukemia Performed Robot‒Assisted Hartmann's Procedure].

The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rectal cancer surgery, was referred to our hospital fo...

The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.

In 2020, the new type of coronal pneumonitis became a pandemic in the world, and has firstly been reported in Wuhan, China. Chest CT is a vital compon...