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Triage

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DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning.

Medical image analysis
In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical tests are commonly referred to during the process, but the misdiagnosi...

Clinical actionability of triaging DNA mismatch repair deficient colorectal cancer from biopsy samples using deep learning.

EBioMedicine
BACKGROUND: We aimed to develop a deep learning (DL) model to predict DNA mismatch repair (MMR) status in colorectal cancers (CRC) based on hematoxylin and eosin-stained whole-slide images (WSIs) and assess its clinical applicability.

Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning-based diagnostic algorithm.

Journal of the American Academy of Dermatology
BACKGROUND: Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of ...

RETRACTED: Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques.

International journal of environmental research and public health
Triaging of medical referrals can be completed using various machine learning techniques, but trained models with historical datasets may not be relevant as the clinical criteria for triaging are regularly updated and changed. This paper proposes the...

Development of practical triage methods for critical trauma patients: machine-learning algorithm for evaluating hybrid operation theatre entry of trauma patients (THETA).

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Hybrid operating rooms benefit patients with severe trauma but have a prerequisite of significant resources. This paper proposes a practical triage method to determine patients that should enter the hybrid operating room considering a limite...

Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms.

Journal of medical imaging and radiation oncology
INTRODUCTION: The primary aim was to develop convolutional neural network (CNN)-based artificial intelligence (AI) models for pneumothorax classification and segmentation for automated chest X-ray (CXR) triaging. A secondary aim was to perform interp...

Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Pediatric sepsis imposes a significant burden of morbidity and mortality among children. While the speedy application of existing supportive care measures can substantially improve outcomes, further improvements in delivering that care require tools ...

Machine learning-based prediction of critical illness in children visiting the emergency department.

PloS one
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...

Deep learning models for triaging hospital head MRI examinations.

Medical image analysis
The growing demand for head magnetic resonance imaging (MRI) examinations, along with a global shortage of radiologists, has led to an increase in the time taken to report head MRI scans in recent years. For many neurological conditions, this delay c...