Virtual replicas of physical objects, processes, or systems that are created using digital technologies, such as computer-aided design (CAD), simulation, and data analytics. In the context of engineering and manufacturing, digital twins are used to model and simulate products, equipment, and manufacturing processes, allowing for optimization, prediction, and analysis of performance and behavior.
Published in Chapter:
Artificial Intelligence in Modern Medical Science: A Promising Practice
Ranjit Barua (OmDayal Group of Institutions, India) and
Sudipto Datta (Indian Institute of Science, Bangalore, India)
Copyright: © 2023
|Pages: 12
DOI: 10.4018/978-1-6684-9189-8.ch001
Abstract
Medical technology powered by artificial intelligence is quickly developing into useful clinical practice solutions. Deep learning algorithms can handle the growing volumes of data produced by mobile monitoring sensors found in wearables, smartphones, and other medical devices. Currently, only a very limited number of clinical practice settings, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging, benefit from the application of artificial intelligence. Patients have been waiting for the deployment of augmented medicine since it gives them more autonomy and more individualized care, but doctors have been resistant because they weren't ready for such a change in clinical practice. The purpose of this study is to glance over recent scientific material and offer a perspective on the advantages, potential benefits, and potential concerns of established artificial intelligence applications in the modern healthcare sector.