Artificial Intelligence Frontiers

Innovations, Challenges, and Applications
1. Auflage 2026
ISBN: 978-1-041-11551-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 232 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advances in Computational Collective Intelligence

Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the 21st century, revolutionizing fields such as finance, healthcare, security, and human-centered decision systems. As AI continues to evolve, its applications increasingly integrate machine learning, deep learning, cognitive sciences, and data-driven analytics. Artificial Intelligence Frontiers: Innovations, Challenges, and Applications presents a comprehensive compilation of cutting-edge research exploring new AI technologies, their applications, and implementation challenges.

The book examines diverse AI applications across multiple domains. It begins with neural networks for financial risk assessment and decision-making, then explores multimodal AI systems that integrate vision, text, and speech to enhance machine cognition. Additional chapters address predictive modeling using Long Short-Term Memory networks and deep learning applications in computer vision, including road lane detection and deepfake detection.

Beyond technical innovations, the book investigates AI's role in healthcare and social sciences, covering perinatal depression analysis and neurodevelopmental disorder diagnosis in India. These contributions demonstrate AI's potential for early detection, improved diagnostics, and data-driven healthcare interventions.

Recognizing the growing importance of responsible AI, subsequent chapters address critical issues of transparency, explainability, privacy, and ethical governance. Discussions on explainable AI, trustworthy human-centric systems, and regulatory frameworks for data protection emphasize the essential balance between technological innovation and ethical accountability.

By consolidating perspectives from researchers, practitioners, and scholars, this book provides readers with comprehensive insights into AI's transformative nature. It serves as an invaluable resource for students, researchers, and professionals seeking to understand the latest advances, current policies, and ethical considerations shaping AI's future.

Zielgruppe

Academic

Autoren/Hrsg.

Saltz, Jeff

Tacheva, Jasmina

Tiwari, Shamik

Jain, Anurag

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement

Inhaltsverzeichnis

1. Neural Networks for Individual Risk Assessment in Financial Decision-Making 2. Multimodal AI: Integrating Vision, Text, and Speech 3. Long Short-Term Memory Model-Based Planet Trajectory Prediction 4. Deep Learning-Powered Road Lane Detection via YOLO Box Predictions 5. Deepfake Detection Using Deep Learning and Machine Learning Algorithms 6. Unveiling Perinatal Depression: Causes, Consequences, and Interventions 7. Recent Trends in AI for Neurodevelopmental Disabilities (NDD) Diagnosis: An Indian Perspective 8. Emerging Technologies to Ensure AI Transparency 9. Bridging Trust and Transparency: Explainability in Human-Centric AI Systems 10. AI, Privacy, and Data Protection in the Age of Industry 5.0: A Comparative Legal Perspective from India and Global Frameworks

Über Autor(innen)

A professor at Syracuse University, Dr. Jeffrey Saltz's research focuses on the socio-technical issues relating to AI and data science, such as how to effectively leverage AI and data science within an organizational context and how teams should work together to "do" data science and AI projects. His more than 20 years of industry information systems experience has often focused on building new teams that leverage emerging technologies to deliver innovative business solutions. In his last corporate role, he worked at JPMorgan Chase. At JPMC, he reported to the firm's Chief Information Officer while helping to drive innovation throughout the firm. He also held several other key technology management positions at the company, including CTO (Consumer and Community Banking Risk Management), Chief Information Architect (Chase Financial Services), global head of eBusiness technology, and vice president of computational technology. He previously served as chief technology officer and principal investor at Goldman Sachs/Goldman Sachs Ventures, where he invested and helped incubate technology start-ups. He started his career as a programmer, project leader, and consulting engineer with Digital Equipment Corp (now part of HP).

Dr. Jasmina Tacheva is an Assistant Professor in the School of Information Studies, Syracuse University. She studied Philosophy, Economics, and German at Canisius College and earned her Ph.D. from the University at Buffalo's (UB) School of Management, where she was part of the NAVIGATE Project, an NSF-sponsored initiative for supporting women in STEM. During her time at UB, she co-organized the Annual Social Sciences and Humanities Symposium and won the 2018 UB World's Challenge with ElevateHer—a data science education project for women in developing countries in collaboration with software engineer Manjusha Raveendran and structural engineer and founder of Women Engineers Pakistan Ramla Qureshi. Her research on the social networks of digital volunteers on Twitter won the best poster award at that year's Northeast Regional Conference on Complex Systems.

Dr. Shamik Tiwari, Dean and Professor at the School of Computer Science & Engineering, IILM University, India, brings over two decades of comprehensive expertise encompassing research, teaching, and administration. His leading-edge research has earned him recognition as one of the world's top 2% of research scientists, acknowledged by Stanford University in 2023 & 2024. Dr. Tiwari's proficiency extends across diverse domains, including data analytics, statistical modeling, predictive modeling, machine learning, deep learning, NLP, image processing, computer vision, and data visualization. Renowned in his field, he has made significant contributions to health diagnostics, particularly in critical areas such as COVID-19, Alzheimer's disease, dermatologist-level classification of skin cancer, and arrhythmia. A notable project led by Dr. Tiwari involves the development of a "non-invasive diagnostic tool for diabetic retinopathy using lightweight intelligent applications and fundus photography." This pioneering initiative, recommended and funded by BIRAC, Department of Biotechnology (DBT), Government of India, highlights his dedication to advancing healthcare solutions.

A professor and the head of the Examination Department at IILM University, Dr. Anurag Jain is a highly motivated and results-oriented professional with a diverse background and a proven track record of success. Equipped with strong analytical, problem-solving, and communication skills, he excels in leveraging his expertise to drive organizational growth and exceed objectives. He has been in academia for the past 23 years. Dr. Jain's research interests lie in the applications of machine learning and deep learning. He has published over 80 research papers, 10 patents, and one book. Of these, more than 40 papers are published in Scopus/SCI-SCIE indexed journals, and 16 papers are presented at international conferences. To date, 14 M. Tech. students and four Ph.D. students have successfully defended their dissertations under his guidance. He has also successfully completed a government-funded project.