AI and Intelligent Decision Support System
This special session is organised and supported by the following educational partner
Teesside University, UK
Session Chair:
- Dr Hiba Alsmadi, Teesside University, UK
Session Co-Chair:
- Dr Ala Alkafri, Teesside University, UK
Scientific Committee:
Dr Tariq Alwada’n, Teesside University, UK
Dr Wael Al-Karaki, Teesside University, UK
Synopsis:
In an era of rapid technological advancement, AI and Intelligent Decision Support Systems have emerged as indispensable tools across various industries. These systems leverage cutting-edge algorithms and data-driven insights to assist professionals in making informed choices, optimizing processes, and achieving unparalleled efficiency.
This transformative technology has found applications in fields as diverse as healthcare, finance, manufacturing, and beyond. By harnessing the power of machine learning, natural language processing, and predictive analytics, organizations can now navigate complex datasets and extract actionable intelligence in real-time. From medical diagnostics that augment clinical expertise to financial platforms that enhance investment strategies, the potential applications of AI and Intelligent Decision Support Systems are boundless. They empower professionals to uncover hidden patterns, mitigate risks, and elevate decision-making to new heights of precision and accuracy.
Topics:
- Explainable AI for Decision Support
- Ethical Considerations in AI-Driven Decision Support
- AI-Powered Predictive Maintenance
- Multi-Agent Systems for Decision Support
- Natural Language Processing for Decision Support
- Personalized Medicine and Healthcare Decision Support
- Anomaly Detection in Financial Transactions
- Optimization Techniques in Supply Chain Management
- AI-Enhanced Cybersecurity Decision Support
- Human-AI Interaction in Decision Support Systems
- AI in Environmental Decision Support
- AI for Personal Financial Planning
- AI in Educational Decision Support
- AI for Smart Cities and Urban Planning
- AI in Customer Service and Support Systems
Paper Submission
Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.