Bøker av Loveleen Gaur

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.

Transportation typically entails crucial "e;life-death"e; choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence.Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment.The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.

Apart from technological introduction to deepfakes concept, the book details algorithms to detect deepfakes, techniques for identifying manipulated content and identifying face swap, generative adversarial neural networks, media forensic techniques, deep learning architectures, forensic analysis of deepfakes and so forth.