Pantea Keikhosrokiani – författare

Perspectives in the Development of Mobile Medical Information Systems: Life Cycle, Management, Methodological Approach and Application discusses System Development Life Cycle (SDLC) thoroughly, focusing on Mobile Healthcare Information Systems (M-HIS). Covering all aspect of M-HIS development, the book moves from modeling, assessment, and design phases towards prototype phase. Topics such as mobile healthcare information system requirements, model identification, user behavior, system analysis and design are all discussed. Additionally, it covers the construction, coding and testing of a new system, and encompasses a discussion on future directions of the field.

Based on an existing mobile cardiac emergency system used as a real case throughout the chapters, and unifying and clarifying the various processes and concepts of SDLC for M-HIS, this book is a valuable source for medical informaticians, graduate students and several members of biomedical and medical fields interested in medical information systems.

Presents a system development life cycle that can be used for developing different kinds of systems others than health related and also can be used for educational purposes Includes behavioral studies in the system development life cycle to assist in the design of systems with consideration of users' behavior, which is even more important for medical systems Uses a real mobile cardiac emergency system as an example for systems development

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems

Habit-based Behavior Change Medical Information Support System and Artificial Intelligence: Theories, Methods, and Data Analytics Approach provides a guideline to design and implement Habit-based Behavior Change Support Systems (HBCSS) which can change patient’s unhealthy habits to prevent the development of diseases. It presents theories, methods, management, and data analytics approach required to design, implement, and prescribe the use of HBCSS for several diseases’ management.It discusses topics such as theories of behavior change, ontologies and knowledge management, data mining, privacy and security, descriptive and prescription analytics. In addition, it discusses how to measure habit-change, future directions of the field, and case studies based on real-world examples.It is a valuable resource for clinicians, researchers, students, and member of the biomedical and medical fields who want to learn more about the use of medical systems to improve patients’ health.Discusses how habit-change features can be added to medical information systems to change patient’s unhealthy habitsDescribes the habit-change life cycle and framework so that readers can develop their own systemOutlines how data analytics features are used to diagnose and predict unhealthy habits and prescribe changes to improve overall health of patients

This two-volume set constitutes the refereed proceedings of the First Nordic Conference on , Digital Health and Wireless Solutions, NCDHWS 2024, held in Oulu, Finland, during May 7–8, 2024.The 51 full papers included in this book together with 7 short papers were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows:Part I: Remote Care and Health Connectivity Architectures in 6G Era.- User Experience and Citizen Data.- Digitalization in Health Education.- Digital Health Innovations.- Digital Care Pathways.Part II: Clinical Decision Support and Medical AI.- Digital Care Pathways.- Novel Sensors and Bioinformatics.- Health Technology Assessment and Impact Evaluation.- Wireless Technologies and Medical Devices.This book is open access.

This two-volume set constitutes the refereed proceedings of the First Nordic Conference on , Digital Health and Wireless Solutions, NCDHWS 2024, held in Oulu, Finland, during May 7–8, 2024.The 51 full papers included in this book together with 7 short papers were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows:Part I: Remote Care and Health Connectivity Architectures in 6G Era.- User Experience and Citizen Data.- Digitalization in Health Education.- Digital Health Innovations.- Digital Care Pathways.Part II: Clinical Decision Support and Medical AI.- Digital Care Pathways.- Novel Sensors and Bioinformatics.- Health Technology Assessment and Impact Evaluation.- Wireless Technologies and Medical Devices.This book is open access.