Author Profile

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.

About The Book

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.

Table of Contents

Preface
1.
INTRODUCTION TO MEDICAL APPLICATIONS OF ARTIFICIAL INTELLIGENCE .....1
1.1 Introduction
1.2 A Bit of History
2.
OVERVIEW OF ARTIFICIAL INTELLIGENCE..................................................................5
2.1 Introduction to Artificial Intelligence
2.2 Machine Learning
2.3 Support Vector Machines
2.4 Neural Networks
2.5 Naïve Bayesian Classifier
2.6 Hidden Markov Models
2.7 k-Means Clustering
2.8 Principal Component Analysis
3.
DATA MINING METHODS WITH EXAMPLE
APPLICATIONS TO THE MEDICAL DOMAIN .............................................................24
3.1 Introduction
3.2 Overview of Machine Learning and Data Mining
3.3 Machine Learning and Data Mining Resources
3.4 Example/Illustrative Medical Applications
3.5 Conclusions
4.
COMPUTATIONAL INTELLIGENCE TECHNIQUES AND AREAS OF
THEIR APPLICATIONS IN MEDICINE ..........................................................................43
4.1 Introduction
4.2 Fuzzy Logic
4.3 Genetic Algorithm
4.4 ANNs
4.5 Conclusion
5.
SATISFICING OR THE RIGHT INFORMATION AT THE RIGHT TIME........................57
5.1 Introduction
6.
SOFT TISSUE CHARACTERIZATION USING GENETIC ALGORITHM .......................64
6.1 Introduction
6.2 Biomechanical Models
Contents
6.3 GA
6.4 Performance Analysis
6.5 Conclusions
7.
MACHINES AND WAVELET TRANSFORM IN ELECTROENCEPHALOGRAM
SIGNAL CLASSIFICATION.............................................................................................78
7.1 Introduction
7.2 Data Analysis
7.3 Support Vector Machines
7.4 Description of Multiclass Methods
7.5 Experimental Results
7.6 Conclusion
8.
BUILDING NAÏVE BAYES CLASSIFIERS WITH HIGH DIMENSIONAL AND
SMALL-SIZED DATA SETS ............................................................................................95
8.1 Introduction
8.2 Naïve Bayes Classifier
8.3 Experiments
8.4 Discussions and Problems
8.5 Conclusion and Future Work
9.
PREDICTING TOXICITY OF CHEMICALS COMPUTATIONALLY..............................114
9.1 Introduction
9.2 Data Set
9.3 Preprocessing and Computation
9.4 RF with Boosting Algorithm
9.5 Toxicity Prediction Using Bayesian Classifiers
9.6 Concluding Remarks
10.
CANCER PREDICTION METHODOLOGY USING AN
ENHANCED ARTIFICIAL NEURAL NETWORK...........................................................127
10.1 Introduction
10.2 Review of Related Research
10.3 Dominant Gene Prediction Using ANN
10.4 Results and Discussion
10.5 Discussion
10.6 Conclusion
11.
A SYSTEM FOR MELANOMA DIAGNOSIS
BASED ON DATA MINING............................................................................................139
11.1 Introduction
11.2 Data Set
11.3 Rule Induction and Validation
11.4 Optimization of the ABCD Formula
11.5 Internet Melanoma Diagnosing and Learning System
11.6 Synthetic Skin Lesions
11.7 Conclusions
12.
IMPLEMENTATION AND OPTIMIZATION................................................................146
12.1 Introduction
12.2 Retinal Layer Detection in OCT Images
12.3 Experiments and Results
12.4 Computational Optimizations to the 3-D Model
12.5 Conclusions
13.
DEEP LEARNING FOR THE SEMIAUTOMATED ANALYSIS OF PAP SMEARS.......162
13.1 Introduction
13.2 Background and Related Work
13.3 Processing and Data Analysis
13.4 Applying SVM
13.5 Applying DBNs
13.6 Conclusion and Discussions
14.
A PENALIZED FUZZY CLUSTERING ALGORITHM.....................................................182
14.1 Introduction
14.2 Penalized Fuzzy Clustering Algorithms
14.3 Theoretical Analysis on Penalized Fuzzy Clustering Algorithms
14.4 Numerical Comparisons
14.5 Application to Ophthalmological MRI Segmentation
14.6 Conclusion
15.
UNCERTAINTY, SAFETY, AND PERFORMANCE........................................................193
15.1 Introduction
15.2 Method
15.3 Results
15.4 Discussion and Outcomes
16.
CLINICAL DECISION SUPPORT IN MEDICINE: A SURVEY OF CURRENT
STATE-OF-THE-ART IMPLEMENTATIONS ...............................................................204
16.1 Introduction
16.2 Case-Based Narrative Review of Selected Clinical Support Systems (2003–2012)
16.3 Summary and Conclusions
16.4 Future Directions
17.
FUZZY NAÏVE BAYESIAN APPROACH FOR MEDICAL DECISION SUPPORT .......220
17.1 Introduction
17.2 Overview of Modeling Techniques
17.3 Why FST is Useful
17.4 Conventional Naïve Bayes
17.5 Fuzzy Naïve Bayes
17.6 Sources of Fuzziness in Patient Data
17.7 Other Fuzzy Set Theoretic Approaches
17.8 Directions for Future Work
18.
APPROACHES FOR ESTABLISHING METHODOLOGIES IN METABOLOMIC
STUDIES FOR CLINICAL DIAGNOSTICS....................................................................228
18.1 Introduction
18.2 Medical Applications of Analytical Chemistry Sensors and Instruments
18.3 Introduction to Analytical Instrumentation for Clinical Applications
18.4 Applications of Advanced Data Analysis to Metabolite Data Sets
18.5 Machine Learning Applications for Metabolomics
on Hyphenated Analytical Chemistry Tools
18.6 Clinical Applications of AI Analysis of Metabolite Content
18.7 Future Outlook on AI in Chemometric Analysis
18.8 Final Words
19.
MEDICAL APPLICATIONS OF ARTIFICIAL INTELLIGENCE.....................................250
19.1 Introduction
19.2 Background and Related Work
19.3 Discretization Methods
19.4 Experiments
19.5 Conclusion
20.
A CRASH INTRODUCTION TO AMBIENT ASSISTED LIVING..................................260
20.1 From Traditional Domotics to Smart Houses
20.2 AAL
20.3 Localization for Context Awareness
20.4 Sensors and Actuators
20.5 Biometrics Sensors
20.6 Interfaces and Ergonomics
20.7 Robotic Companions
20.8 Architecture Design
20.9 Conclusions
Bibliography..................................................................................................................280
Index.............................................................................................................................297