Advances in healthcare technologies have offered real-time guidance and technical assistance for diagnosis, monitoring, operation, and interventions. The development of artificial intelligence, machine learning, internet of things technology, and smart computing techniques are crucial in today's healthcare environment as they provide frictionless and transparent financial transactions and improve the overall healthcare experience. This, in turn, has far-reaching effects on economic, psychological, educational, and organizational improvements in the way we work, teach, learn, and provide care. These advances must be studied further in order to ensure they are adapted and utilized appropriately. Mathematical Modeling for Smart Healthcare Systems presents the latest research findings, ideas, innovations, developments, and applications in the field of modeling for healthcare systems. Furthermore, it presents the application of innovative techniques to complex problems in the case of healthcare. Covering a range of topics such as artificial intelligence, deep learning, and personalized healthcare services, this reference work is crucial for engineers, healthcare professionals, researchers, academicians, scholars, practitioners, instructors, and students.

As old age is increasing globally, some challenges arise such as multimorbidity, a unique medical condition that has multiple potential complications and thus needs high-quality care directed by qualified healthcare providers. Multimorbidity is an important daily challenge to internists worldwide due to its many difficulties. Junior physicians dealing with multimorbidity must have the knowledge to practice high-quality care for their elderly patients. Cases on Multimorbidity and Its Impact on Elderly Patients considers approaches to manage multimorbidity and its unique complications and challenges to aid in appropriate daily decision making. Covering key topics such as weight loss, aging, and frailty, this reference work is ideal for medical professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.

Within the past decade, we have witnessed an increased adoption of emerging technologies as well as the exponential pace of scientific discoveries within all industries. The level of digital innovation and digital transformation experienced in healthcare and life sciences has been markedly accelerated by the COVID-19 pandemic. There is a new sense of urgency to design and develop a new global health ecosystem that is more suitable for the digital era and future generations. Deploying precision medicine solutions that can redefine the way we diagnose and treat disease, as well as shift the focus towards a customized human-centered approach, such as those offered by personalized medicine, can be a viable sustainable model. Digital Identity in the New Era of Personalized Medicine highlights the latest trends in precision medicine and the important role digital identity plays in upholding ethical values, safeguarding human rights, and practicing responsible personalized medicine. It provides an overview of the current healthcare legal and regulatory landscapes as well as some of the major challenges and opportunities we face in this digital, virtual, and precision medicine-powered era. Covering topics such as data-centric compliance, global health, and identity management, this book is an essential resource for doctors, healthcare administration, academicians, clinicians, health and bio-tech executives, researchers, medical professionals, medical engineers, medical students, and government officials looking for a resource that addresses challenges in healthcare including trust, privacy, data integrity, and ownership.