Advances In Artificial Intelligence Empowered Decision Support Systems
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Advances in Artificial Intelligence-Empowered Decision Support Systems
Author: George A. Tsihrintzis
language: en
Publisher: Springer Nature
Release Date: 2024-06-27
Decision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues. DSSs have proven to be particularly useful at the strategic level, while they usually require only limited computer-proficiency skills from their users. Although DSSs have been under development and use for several decades, recent advances in both Software Engineering technologies and Artificial Intelligence (AI) methodologies have heralded new avenues for research and development in this field. This book exposes its readers to some of the most significant Advances in Artificial Intelligence-Empowered Decision Support Systems. It consists of an editorial note and an additional sixteen (16) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. The chapters are organized into five parts, namely (i) AI-Empowered DSS in Medical Diagnosis and Biology, (ii) AI-Empowered DSS in Healthcare and Health Insurance, (iii) AI-Empowered DSS in Urban Matters, (iv) Various Applications of AI-Empowered DSS, and (v) Novel AI-Empowered Methodologies in Decision Making. Targeted toward academics, researchers, practitioners, and students in Computer Science, Artificial Intelligence, and Management, this book is also accessible to individuals from other disciplines interested in the cutting-edge developments of AI-empowered DSS technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them.
Artificial Intelligence-Empowered Bio-medical Applications
Author: Dimitrios P. Panagoulias
language: en
Publisher: Springer Nature
Release Date: 2025-07-19
The book delves into advancements in personalized medicine, highlighting the transition from generalized treatments to tailored strategies through AI and machine learning. It first emphasizes the role of biomarkers in training predictive models and neural networks, enhancing disease diagnosis and patient management. It then explores AI-driven healthcare systems, particularly the use of microservices to improve scalability and management. Additionally, it examines regulatory challenges, the need for AI explainability, and the PINXEL framework, which defines explainability requirements using the technology acceptance model (TAM) and the diffusion of innovation theory (DOI). Furthermore, the book evaluates the capabilities of large language models, including ChatGPT and GPT-4V, in medical applications, with a focus on diagnosis and structured assessments in general pathology. Lastly, it introduces an AI-powered system for primary care diagnosis that integrates language models, machine learning, and rule-based systems. The interactive AI assistants “Med|Primary AI assistant” and “Dermacen Analytica” leverage natural language processing, image analysis, and multi-modal AI to enhance patient interactions and provide healthcare professionals with high-accuracy, personalized diagnostic support. By taking a holistic approach, the book underscores the integration of AI into healthcare, aiming to support medical professionals in patient diagnosis and management with precision and adaptability.
Extended Selected Papers of the 14th International Conference on Information, Intelligence, Systems, and Applications
Author: Nikolaos Bourbakis
language: en
Publisher: Springer Nature
Release Date: 2024-08-13
This book includes extended versions of selected research works that were presented at the 14th International Conference on Information, Intelligence, Systems, and Applications (IISA2023), Volos, Greece, 10–12 July 2024 (https://www.easyacademia.org/iisa2023) along with additional relevant papers by invited authors. Information is widely available and accessible but frequently leads to information overload and overexposure and the effort for coding, storing, hiding, securing, transmitting, and retrieving it may be excessive. Intelligence, inspired by biological and other paradigms, is required to manage information and extract knowledge from it. Information and multimedia systems, with an increasing level of intelligence, are being developed that incorporate these advances. As a result, new technologies, protocols, and novel applications are emerging. In turn, the novel applications lead to the collection of new information, and the “Information à Intelligence à Systems à Applications” circle is repeated at ever higher levels. These works cover a broad spectrum of topics from both novelties in theory and advanced methodologies as well as novel applications in energy, agriculture, medicine, forensics, healthcare, education, tourism, inspection, traffic, and software engineering. Targeted towards academicians, researchers, practitioners, and students in computer science and artificial intelligence, this work is also accessible to individuals from other disciplines interested in the cutting-edge developments of information, intelligence, systems, and applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them.