This book takes an interdisciplinary approach by covering topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided in this book. Key Features Covers computational Intelligence techniques like artificial neural networks, deep neural networks, and optimization algorithms for Healthcare systems Provides easy understanding for concepts like signal and image filtering techniques Includes discussion over data preprocessing and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-ray, FMRI, CT) datasets Describes evolution parameters such as accuracy, precision, and recall etc. This book is aimed at researchers and graduate students in medical signal and image processing, machine and deep learning, and healthcare technologies.

Recent advancements in artificial intelligence (AI) and machine learning (ML) have made previously inaccessible pathways available for enhancing clinical results, reducing the costs of providing medical treatment, and increasing the health of the general public. Technology related to artificial intelligence have the potential to change both the clinical care that is provided to patients and the administrative processes that are followed within healthcare delivery organisations (HDO). The ever-increasing amount and complexity of data relevant to healthcare provides an adequate context for the application of artificial intelligence and machine learning. This setting is supplied by the ever-increasing number of data. It is crucial to keep in mind that artificial intelligence (AI) is not a single technology but rather a group of technologies that can carry out a number of duties. It is important to keep in mind that AI is not a single technology since it is not a singular technology. The following is a list of some of the uses of artificial intelligence in the healthcare industry, however this is by no means a complete list

CONTENTS CLASSIFICATION OF HEART ATTACK RISKS WITH ARTIFICIAL INTELLIGENCE METHODS Ezgi DEMİR IMPROVING PATIENT SERVICES IN HEALTHCARE SYSTEMS: OPTIMIZATION OF APPOINTMENT SCHEDULING Uğur ELİİYİ DIGITAL AGE IN HEALTH SERVICES: WEARABLE TECHNOLOGIES, BLOCKCHAIN TECHNOLOGY AND ARTIFICIAL INTELLIGENCE Mehmet ÇİĞDEM – Aygül YANIK THE IMPORTANCE OF ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT Hatice AĞRALI NURSING AND MIDWIFERY IN THE WORLD OF ARTIFICIAL INTELLIGENCE Esma DEMİREZEN THE IMPACT OF MOBILE HEALTH (M-HEALTH) AND ELECTRONIC HEALTH (E-HEALTH) APPLICATIONS ON HEALTH CARE MANAGEMENT Gamze YORGANCIOĞLU TARCAN – Bülent SAPAZ VOS VIEWER ANALYSIS OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE AND ECONOMICS Melike TORUN

Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.

The application of artificial intelligence in networks and systems is a rapidly evolving field that has the potential to transform a wide range of industries. The refereed proceedings in this book is from the Artificial Intelligence Application in Networks and Systems session of the Computer Science Online Conference 2023 (CSOC 2023), which was held online in April 2023. The section brings together experts from different fields to present their research and discuss the latest trends and challenges. One of the key themes in this section is the development of intelligent systems that can learn, adapt, and optimize their performance in real time. Researchers are exploring how AI algorithms can be used to create autonomous networks and systems that can make decisions without human intervention. Furthermore, this section highlights the use of AI in improving network performance and efficiency. Researchers are exploring how AI algorithms can be used to optimize network routing, reduce congestion, and improve the quality of service. These efforts can help organizations save costs and improve user experience.

In the field of health, digital health has assumed significant importance in recent years due to its contribution to enhancing the overall healthcare system performance in terms of alleviating the ever-growing pressure on the healthcare system, reducing healthcare costs, improving working conditions and job satisfaction of health professionals, improving patients’ satisfaction, and providing a holistic view of patient health through access to data and giving patients more control over their health. Therefore, it is of vital importance to understand the overwhelming possibilities and promise it can offer for better health services. Similarly, exploring barriers to digital health engagement is an important tool to guarantee an effective adoption and transition that can meet all healthcare stakeholders’ objectives. Integrating Digital Health Strategies for Effective Administration explores recent writings and original research findings in the field of digital health with a special focus on digital health adoption strategies and challenges. This book is intellectually situated between digital health management and digital health technologies. Covering topics such as digital health literacy, machine learning, and procedural law, this premier reference source is an essential resource for app developers, healthcare administrators, healthcare professionals, students and educators of higher education, researchers, and academicians.

This book constitutes the refereed proceedings of five International Workshops held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022, virtually and in Hersonissos, Crete, Greece, in June 2022: the 11th Mining Humanistic Data Workshop (MHDW 2022); the 7th 5G-Putting Intelligence to the Network Edge Workshop (5G-PINE 2022); the 1st workshop on AI in Energy, Building and Micro-Grids (AIBMG 2022); the 1st Workshop/Special Session on Machine Learning and Big Data in Health Care (ML@HC 2022); and the 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics (AIBEI 2022). The 35 full papers presented at these workshops were carefully reviewed and selected from 74 submissions.