In the media and entertainment industry, the infusion of Artificial Intelligence has set the stage for a remarkable change. AI has emerged as a formidable force in the realms of game development, movie production, and advertising, innovating creative processes across industries. AI has become a catalyst in the media and entertainment sector, sparking strategic investments and anchoring a determined pursuit to satisfy evergrowing viewer demands. In this era of innovation, robots and augmented intelligence have become the architects of unforgettable, next-generation consumer experiences. Giants in both the media and entertainment and technology spheres, including Blizzard Entertainment, Walt Disney World, Google, Microsoft, and Intel, have converged their expertise to craft, launch, and refine a plethora of AI-driven innovations, propelling the industry into uncharted territories of imagination and spectacle. Artificial Intelligence plays a pivotal role in transitioning from generic, uniform content to personalised experiences tailored for individualistic approach. Utilising sophisticated algorithms, AI platforms analyse user sentiments, behaviours and engagement patterns to curate tailored content, news feed, videos, articles and advertisements. This book aims at understanding different viewpoints from authors on Artificial Intelligence, technology and the contemporary media scenario. Looking at it from a modern outlook, it won't be justified on our part to define new media through some hardcore definition as such. With the onset of the 'latest' and 'what was new yesterday not being new today', the lines have become blurred and the system itself is expanding its wings at a rate comparable to universal expansion (just kidding). The more we think about this concept of New Media, the more we feel as to how tremendous it is! Two words 'New' and 'Media' both with well defined meanings merge and together we get a combination which is for the entire world to explore. It is more than just a media, it's an extension of ourselves. New Media encompasses all sorts of interaction between new technology and established media form to start with and goes way beyond that to bringing and visualising what could be the next new cool, thereby encompassing everything that we have the capacity to think of, if we look at it from a neutral perspective. The very definition of new media is less settled upon, known and identified. It spans a complex path with computer sitting at it's locus of convergence. This book delves into the profound upheaval taking place at the junction of artificial intelligence and the media industry. As AI technologies advance, they are changing the way content is created, disseminated, consumed, and even sold. From newsrooms to social media platforms, AI is creating new opportunities while also posing distinct obstacles.
Dr. Richard Shepherd is an Associate Professor in the Department of Computer Science at Louisiana State University. He earned his Ph.D. and M.S. in Computer Science at the University of Delaware, and his B.S. in Computer Science at Virginia Commonwealth University. David has since worked as a postdoctoral fellow in the Department of Computer Science at the University of British Columbia, built sweat equity as employee #9 at Tasktop Technologies, and risen to Senior Principal Scientist at ABB Corporate Research. His research has produced tools that have been used by thousands, innovations that have been featured in the popular press, and practical ideas that have won business plan competitions. Dr. Shepherd currently serves as the Co-Editor-in-Chief of the Journal of Systems & Software. His current work focuses on enabling end-user programming for industrial machines and increasing diversity in computer science. His research interests include data mining, deep learning, bioinformatics, medical image analysis, and graph learning. He is dedicated to the interdisciplinary study of artificial intelligence (AI) in healthcare and medicine. He focuses on utilizing advanced computational techniques including data mining, machine learning, and deep learning to address critical biomedical challenges such as AI fairness and multimodal learning for robust diseases screening. The objective is to enhance the understanding, diagnosis and clinical management of human diseases through cutting-edge AI-driven tools and methodologies.
Preface
1. INTRODUCTION TO MEDICAL APPLICATIONS OF ARTIFICIAL INTELLIGENCE
2. OVERVIEW OF ARTIFICIAL INTELLIGENCE
3. DATA MINING METHODS WITH EXAMPLE APPLICATIONS TO THE MEDICAL DOMAIN
4. COMPUTATIONAL INTELLIGENCE TECHNIQUES AND AREAS OF THEIR APPLICATIONS IN MEDICINE
5. SATISFICING OR THE RIGHT INFORMATION AT THE RIGHT TIME
6. SOFT TISSUE CHARACTERIZATION USING GENETIC ALGORITHM
7. MACHINES AND WAVELET TRANSFORM IN ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION
8. BUILDING NAÏVE BAYES CLASSIFIERS WITH HIGH DIMENSIONAL AND SMALL-SIZED DATA SETS
9. PREDICTING TOXICITY OF CHEMICALS COMPUTATIONALLY
10. CANCER PREDICTION METHODOLOGY USING AN ENHANCED ARTIFICIAL NEURAL NETWORK
11. A SYSTEM FOR MELANOMA DIAGNOSIS BASED ON DATA MINING
12. IMPLEMENTATION AND OPTIMIZATION
13. DEEP LEARNING FOR THE SEMIAUTOMATED ANALYSIS OF PAP SMEARS
14. A PENALIZED FUZZY CLUSTERING ALGORITHM
15. UNCERTAINTY, SAFETY, AND PERFORMANCE
16. CLINICAL DECISION SUPPORT IN MEDICINE: A SURVEY OF CURRENT STATE-OF-THE-ART IMPLEMENTATIONS
17. FUZZY NAÏVE BAYESIAN APPROACH FOR MEDICAL DECISION SUPPORT
18. APPROACHES FOR ESTABLISHING METHODOLOGIES IN METABOLOMIC STUDIES FOR CLINICAL DIAGNOSTICS
19. MEDICAL APPLICATIONS OF ARTIFICIAL INTELLIGENCE
20. A CRASH INTRODUCTION TO AMBIENT ASSISTED LIVING
Bibliography
Index
$280.00