Tag: technology
Extubation Failure Risk Prediction Model Using Bedside Ultrasound
We have established a risk prediction model for extubation failure in mechanically ventilated ICU patients. This risk model base on bedside ultrasound parameters provides valuable insights for identifying high-risk patients... read more
Predicting ICU Admission in COVID-19-Infected Pregnant Women Using Machine Learning
Routinely collected clinical and laboratory data of COVID-19-infected pregnant women may help recognize high-risk groups who are more liable for complications and more severe course or prognosis and require an ICU admission.... read more
Prediction of Prolonged Mechanical Ventilation in the ICU via Machine Learning
Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary complications such as nosocomial infections, and effective triage of hospital... read more
An Optimal Antibiotic Selection Framework for Sepsis Patients Using AI
In this work we present OptAB, the first completely data-driven online-updateable antibiotic selection model based on Artificial Intelligence (AI) for Sepsis patients accounting for side-effects. OptAB performs an iterative... read more
AI Interpretation of Chest Radiographs in the ICU. Ready for Prime Time?
Chest radiography (CXR) is the primary tool to visualize thoracic pathologies in the ICU. However, accurate interpretation of CXRs is challenging, even when imaging is performed under optimal conditions. This results... read more
Improving Patient Outcomes: Sepsis Protocols and Rapid Host Response Technologies
Patients come into the emergency department (ED) with symptoms, not diagnoses. That’s when time is of the essence. Clinicians must quickly triage patients and establish an appropriate care pathway to obtain the best possible... read more
ECMO in the Adult Patient (Core Critical Care)
Extracorporeal membrane oxygenation (ECMO) is developing rapidly, and is now part of the toolkit for the management of all patients with severe respiratory or cardiac failure. Clinicians of all disciplines are in need of... read more
Army Scientists’ Technique for Early Sepsis Detection in Burn Patients Submitted to FDA
A new invention developed at the U.S. Army Medical Research and Development Command uses an artificial intelligence machine learning algorithm to identify whether burn patients are at risk of experiencing life-threatening... read more
Sepsis Mortality Prediction in ICU Patients Using Machine Learning
This study has achieved significant advancements in predicting sepsis outcomes by utilizing advanced machine learning techniques and sophisticated data preprocessing methods. These methods include data grouping and effective... read more
AI to Predicting Mortality Risk in ICU Patients with AKI
To address the limitations of early acute kidney injury (AKI) prediction, researchers have increasingly turned to machine learning methods. However, the success of these models hinges on the selection of relevant features.... read more
Scientific Study Validates Usability of Post-ICU Digital Diary for Families of ICU Patients
In a groundbreaking pilot study, "The usability of a digital diary from the perspectives of intensive care patients’ relatives", researchers have unequivocally confirmed the practicality and effectiveness of Post-ICU for... read more
Ground-breaking New AI Technology for Severe Sepsis Rapid Identification
ASEP Medical Holdings Inc. announced the ground-breaking use of artificial intelligence (AI) to rapidly identify infections at increased risk of severe sepsis. The method was developed by the Hancock Lab, under the guidance... read more
Infusion Management Software Can Seamlessly Connect Thousands Pumps Across Facilities
A newly-launched next-generation infusion management platform provides organizations with a blend of real-time views and retrospective reporting capabilities, enhancing the understanding of their infusion pump fleet and associated... read more
High Speed Blood Flow Measurements Enabled by LW-iDCS
In this work we have demonstrated the development of long wavelength, interferometric diffuse correlation spectroscopy. Using a fiber optic probe with collocated detection fibers, we were able to directly compare measured... read more
Deep Learning-based Electrocardiographic Screening for Chronic Kidney Disease
Undiagnosed chronic kidney disease (CKD) is a common and usually asymptomatic disorder that causes a high burden of morbidity and early mortality worldwide. We developed a deep learning model for CKD screening from routinely... read more
