In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we inves...
International journal of nursing education scholarship
Jun 24, 2021
OBJECTIVES: This manuscript describes the application of deep learning to physiology education of Student Registered Nurse Anesthetists (SRNA) and the benefits thereof. A strong foundation in physiology and the ability to apply this knowledge to chal...
The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic ...
Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell dea...
BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values ca...
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...
INTRODUCTION AND HYPOTHESIS: Surgery for pelvic organ prolapse (POP) has high recurrence rates. Long-term anatomical and patient-reported outcomes after pelvic floor repair are therefore required.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Jun 23, 2021
Machine Learning (ML) has been proposed for tissue fate prediction after acute ischemic stroke (AIS), with the aim to help treatment decision and patient management. We compared three different ML models to the clinical method based on diffusion-perf...
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.