by Loveleen Gaur, Noor Zaman Jhanjhi
The healthcare industry is starting to
adopt digital twins to improve personalized medicine, healthcare
organization performance, and new medicine and devices. These digital
twins can create useful models based on information from wearable
devices, omics, and patient records to connect the dots across processes
that span patients, doctors, and healthcare organizations as well as
drug and device manufacturers. Digital twins are digital representations
of human physiology built on computer models. The use of digital twins
in healthcare is revolutionizing clinical processes and hospital
management by enhancing medical care with digital tracking and advancing
modelling of the human body. These tools are of great help to
researchers in studying diseases, new drugs, and medical devices.
Digital Twins and Healthcare: Trends, Techniques, and Challenges
facilitates the advancement and knowledge dissemination in methodologies
and applications of digital twins in the healthcare and medicine
fields. This book raises interest and awareness of the uses of digital
twins in healthcare in the research community. Covering topics such as
deep neural network, edge computing, and transfer learning method, this
premier reference source is an essential resource for hospital
administrators, pharmacists, medical professionals, IT consultants,
students and educators of higher education, librarians, and researchers.
