AI Medical Compendium Topic:
Prospective Studies

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AI-ENABLED ASSESSMENT OF CARDIAC FUNCTION AND VIDEO QUALITY IN EMERGENCY DEPARTMENT POINT-OF-CARE ECHOCARDIOGRAMS.

The Journal of emergency medicine
BACKGROUND: The adoption of point-of-care ultrasound (POCUS) has greatly improved the ability to rapidly evaluate unstable emergency department (ED) patients at the bedside. One major use of POCUS is to obtain echocardiograms to assess cardiac functi...

Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.

Journal of telemedicine and telecare
INTRODUCTION: Age-related macular degeneration, diabetic retinopathy, and glaucoma are vision-threatening diseases that are leading causes of vision loss. Many studies have validated deep learning artificial intelligence for image-based diagnosis of ...

Biopsychosocial effects and experience of use of robotic and virtual reality devices in neuromotor rehabilitation: A study protocol.

PloS one
BACKGROUND: Robot-assisted therapy (RAT) and virtual reality (VR)-based neuromotor rehabilitation have shown promising evidence in terms of patient's neuromotor recovery, so far. However, still little is known on the perceived experience of use of ro...

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.

World journal of emergency surgery : WJES
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within ...

Assessment of Helicobacter pylori infection by deep learning based on endoscopic videos in real time.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND AND AIMS: Endoscopic assessment of Helicobacter pylori infection is a simple and effective method. Here, we aimed to develop a deep learning-based system named Intelligent Detection Endoscopic Assistant-Helicobacter pylori (IDEA-HP) to ass...

Accurate detection of arrhythmias on raw electrocardiogram images: An aggregation attention multi-label model for diagnostic assistance.

Medical engineering & physics
BACKGROUND: The low rate of detection of abnormalities has been a major problem with current artificial intelligence-based electrocardiogram diagnostic algorithms, particularly when applied under real-world clinical scenarios.

Predicting anterior cruciate ligament failure load with T* relaxometry and machine learning as a prospective imaging biomarker for revision surgery.

Scientific reports
Non-invasive methods to document healing anterior cruciate ligament (ACL) structural properties could potentially identify patients at risk for revision surgery. The objective was to evaluate machine learning models to predict ACL failure load from m...

A deep-learning algorithm to classify skin lesions from mpox virus infection.

Nature medicine
Undetected infection and delayed isolation of infected individuals are key factors driving the monkeypox virus (now termed mpox virus or MPXV) outbreak. To enable earlier detection of MPXV infection, we developed an image-based deep convolutional neu...

Hospital-wide survey of clinical experience with artificial intelligence applied to daily chest radiographs.

PloS one
PURPOSE: To assess experience with and perceptions of clinical application of artificial intelligence (AI) to chest radiographs among doctors in a single hospital.