AIMC Topic: Prospective Studies
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Deep learning model can improve the diagnosis rate of endoscopic chronic atrophic gastritis: a prospective cohort study.
BMC gastroenterology
Mar 23, 2022
BACKGROUND AND AIMS: Chronic atrophic gastritis (CAG) is a precancerous form of gastric cancer. However, with pathological diagnosis as the gold standard, the sensitivity of endoscopic diagnosis of atrophy is only 42%. We developed a deep learning (D...
Diagnostic Accuracy of Wireless Capsule Endoscopy in Polyp Recognition Using Deep Learning: A Meta-Analysis.
International journal of clinical practice
Mar 19, 2022
AIM: As the completed studies have small sample sizes and different algorithms, a meta-analysis was conducted to assess the accuracy of WCE in identifying polyps using deep learning.
Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Mar 17, 2022
BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed to...
Assessment and counseling to get the best efficiency and effectiveness of the assistive technology (MATCH): Study protocol.
PloS one
Mar 16, 2022
AIMS: To determine the psychosocial impact of assistive technology(AT) based on robotics and artificial intelligence in the life of people with disabilities.
Development of Various Diabetes Prediction Models Using Machine Learning Techniques.
Diabetes & metabolism journal
Mar 11, 2022
BACKGROUND: There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters.
Artificial intelligence in glomerular diseases.
Pediatric nephrology (Berlin, Germany)
Mar 10, 2022
In this narrative review, we focus on the application of artificial intelligence in the clinical history of patients with glomerular disease, digital pathology in kidney biopsy, renal ultrasonography imaging, and prediction of chronic kidney disease ...
Multiparametric Functional MRI of the Kidney: Current State and Future Trends with Deep Learning Approaches.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Mar 10, 2022
BACKGROUND: Until today, assessment of renal function has remained a challenge for modern medicine. In many cases, kidney diseases accompanied by a decrease in renal function remain undetected and unsolved, since neither laboratory tests nor imaging ...
A deep learning-based system for real-time image reporting during esophagogastroduodenoscopy: a multicenter study.
Endoscopy
Mar 10, 2022
BACKGROUND AND STUDY AIMS: Endoscopic reports are essential for the diagnosis and follow-up of gastrointestinal diseases. This study aimed to construct an intelligent system for automatic photo documentation during esophagogastroduodenoscopy (EGD) an...
Technical Feasibility of Supervision of Stretching Exercises by a Humanoid Robot Coach for Chronic Low Back Pain: The R-COOL Randomized Trial.
BioMed research international
Mar 9, 2022
Adherence to exercise programs for chronic low back pain (CLBP) is a major issue. The R-COOL feasibility study evaluated humanoid robot supervision of exercise for CLBP. Aims are as follows: (1) compare stretching sessions between the robot and a phy...
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.
The Lancet. Digital health
Mar 7, 2022
BACKGROUND: Diabetic retinopathy is a leading cause of preventable blindness, especially in low-income and middle-income countries (LMICs). Deep-learning systems have the potential to enhance diabetic retinopathy screenings in these settings, yet pro...
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