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Handbook of Research on Nano-Strategies for Combatting Antimicrobial Resistance and Cancer
Multidrug-resistant bacteria play a significant role in public health by destroying the potency of existing antibiotics. Meanwhile, cancer remains one of the most common health problems that impact society, resulting in many deaths worldwide. Novel strategies are required to combat antimicrobial resistance and create efficient anticancer drugs that could revolutionize treatment. Nanomedicine is one such innovation that plays a significant role in developing alternative and more effective treatment strategies for antimicrobial resistance and cancer theranostics. The Handbook of Research on Nano-Strategies for Combatting Antimicrobial Resistance and Cancer is an essential scholarly resource th...
Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
Ethical Implications of Reshaping Healthcare With Emerging Technologies
Improving quality of life is one of the main advantages of integrating new innovations into medicine. New technologies are revolutionizing medicine and opening new opportunities for patients, doctors, clinics, and companies. The patient's well-being is monitored autonomously by smartphones, digital medical records simplify everyday clinical work, virtual reality is used for treatment, and robots help in the operating room. The new technological possibilities in healthcare not only change patients’ lives, but also the work of doctors, clinics, and companies. In the fields of healthcare and medicine, new technologies can be used for patient communication, health monitoring, or for the treatm...
Advancing the Investigation and Treatment of Sleep Disorders Using AI
There are more than 80 different sleep disorders including insomnia, sleep apnea, restless leg syndrome, hypersomnia, circadian rhythm disorders, and parasomnia. Good sleep is necessary for optimal health and can affect hormone levels and weight. The use of artificial intelligence (AI) and biomedical signals and images can help in healthcare diagnostics that are related to these and other sleep disorders. Advancing the Investigation and Treatment of Sleep Disorders Using AI presents an overview of sleep disorders based on machine intelligence methods in order to learn and explore the latest advancements, developments, methods, systems, futuristic approaches, and algorithms towards sleep diso...
Assistive Technologies for Assessment and Recovery of Neurological Impairments
People with neurological disorders may experience significant problems, isolation, detachment, and passivity while dealing with environmental requests. They constantly rely on caregivers and family assistance, which can create negative outcomes on their quality of life. An emerging way to overcome these issues is assistive technology-based interventions (AT). AT-based programs are designed to fill the gap between human/individual capacities or skills and environmental requests. These technologies can also bring about independence and self-determination and provide people with neurological disorders an active role, positive participation, and an enhanced status in being able to achieve functi...
Innovative Approaches for Nanobiotechnology in Healthcare Systems
Innovative and fusion technologies have shown an incredible ability to improve various aspects of society, such as healthcare systems. Nanobiotechnology is one such technology that is being applied to medical equipment and treatment approaches. Many pharmaceutical and medical companies have begun to count on medical nanotechnology due to its abundant applications and practical uses. Innovative Approaches for Nanobiotechnology in Healthcare Systems is a pivotal reference source that provides insights into a comprehensive collection of novel techniques used for the development of safe drugs using the available resources for diverse deadly diseases. This book discusses the various platforms of nanobiotechnology that are utilized in various fields. It is expected that bionanosytems will play a crucial role in the treatment of human diseases and the improvement of existing healthcare systems. This book is ideal for scientists, biotechnologists, microbiologists, medical professionals, entrepreneurs, policymakers, researchers, academicians, and students.
Emerging Advancements for Virtual and Augmented Reality in Healthcare
Within the last few years, devices that are increasingly capable of offering an immersive experience close to reality have emerged. As devices decrease in size, the interest and application possibilities for them increase. In the healthcare sector, there is an enormous potential for virtual reality development, as this technology allows, on the one hand, the execution of operations or processes at a distance, decoupling realities; and on the other hand, it offers the possibility of simulation for training purposes, whenever there are contexts of risk to the patient or to the health professional. However, virtual reality devices and immersion in virtual environments still requires some improv...
Deep Learning Applications in Medical Imaging
Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.
Handbook of Research on Solving Modern Healthcare Challenges With Gamification
While many fields such as e-learning, business, and marketing have taken advantage of the potential of gamification, the healthcare domain has just started to exploit this emerging trend, still in an ad-hoc fashion. Despite the huge potential of applying gamification on several topics of healthcare, there are scarce theoretical studies regarding methodologies, techniques, specifications, and frameworks. These applications must be examined further as they can be used to solve major healthcare-related challenges such as care plan maintenance, medication adherence, phobias treatment, or patient education. Handbook of Research on Solving Modern Healthcare Challenges With Gamification aims to sha...
Machine Learning in Cancer Research With Applications in Colon Cancer and Big Data Analysis
Cancer continues to be a growing problem as it is the foremost cause of death worldwide, killing millions of people each year. The number of people battling cancer continues to increase, owing to different reasons, such as lifestyle choices. Clinically, determining the cause of cancer is very challenging and often inaccurate. Incorporating efficient and accurate algorithms to detect cancer cases is becoming increasingly beneficial for scientists in computer science and healthcare, as well as a long-term benefit for doctors, patients, clinic practitioners, and more. Specifically, an automation of computation in machine learning could be a solution in the next generation of big data science te...
