Special Issues
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Artificial Intelligence Algorithms and Applications, 2nd Edition

Submission Deadline: 15 March 2026 View: 844 Submit to Special Issue

Guest Editors

Dr. Antonio Sarasa-Cabezuelo

Email: asarasa@ucm.es

Affiliation: Dpt.  Sistemas  Informáticos  y  Computación.  Complutense University of Madrid. Madrid 28040, Spain

Homepage:

Research Interests: artificial intelligence, machine learning, medical informatics, public health, deep learning, generative artificial intelligence

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Summary

Artificial Intelligence (AI) has become a transformative force in technology, driving innovation across diverse sectors. AI algorithms, which form the backbone of intelligent systems, are increasingly applied in areas such as healthcare, robotics, and beyond. The continuous evolution of these algorithms has enabled more accurate predictions, efficient data processing, and the development of autonomous systems, making AI a critical research area. Understanding and advancing AI algorithms is essential for addressing complex real-world challenges, fostering technological growth, and enhancing human-machine collaboration.


Aim and Scope:
This Special Issue aims to explore the latest advancements in AI algorithms and their wide-ranging applications. The focus is on cutting-edge research that contributes to the development, optimization, and practical deployment of AI algorithms. By gathering contributions from experts in the field, this issue seeks to highlight innovative approaches and emerging trends that can drive future developments in AI. The scope includes both theoretical explorations and real-world applications, providing a comprehensive view of the current state and potential of AI technologies.

Suggested Themes:
· Machine learning and deep learning algorithms
· AI in healthcare and medical diagnostics
· Robotics and autonomous systems
· Natural language processing and understanding
· AI-driven cybersecurity solutions
· Reinforcement learning and decision-making systems
· Computer vision and image recognition
· Explainable AI and transparency in algorithms
· AI for smart cities and urban planning
· Human-computer interaction and AI
· AI in supply chain management and logistics
· AI in entertainment and media content creation
· Evolutionary algorithms and optimization techniques
· AI for predictive maintenance and industrial automation
· AI in agriculture and food security


Keywords

artificial intelligence, machine learning, deep learning, autonomous systems, natural language processing, robotics, AI applications.

Published Papers


  • Open Access

    ARTICLE

    TeachSecure-CTI: Adaptive Cybersecurity Curriculum Generation Using Threat Dynamics and AI

    Alaa Tolah
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.074997
    (This article belongs to the Special Issue: Artificial Intelligence Algorithms and Applications, 2nd Edition)
    Abstract The rapidly evolving cybersecurity threat landscape exposes a critical flaw in traditional educational programs where static curricula cannot adapt swiftly to novel attack vectors. This creates a significant gap between theoretical knowledge and the practical defensive capabilities needed in the field. To address this, we propose TeachSecure-CTI, a novel framework for adaptive cybersecurity curriculum generation that integrates real-time Cyber Threat Intelligence (CTI) with AI-driven personalization. Our framework employs a layered architecture featuring a CTI ingestion and clustering module, natural language processing for semantic concept extraction, and a reinforcement learning agent for adaptive content sequencing. By… More >

  • Open Access

    REVIEW

    AI Agents in Finance and Fintech: A Scientific Review of Agent-Based Systems, Applications, and Future Horizons

    Maryan Rizinski, Dimitar Trajanov
    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-34, 2026, DOI:10.32604/cmc.2025.069678
    (This article belongs to the Special Issue: Artificial Intelligence Algorithms and Applications, 2nd Edition)
    Abstract Artificial intelligence (AI) is reshaping financial systems and services, as intelligent AI agents increasingly form the foundation of autonomous, goal-driven systems capable of reasoning, learning, and action. This review synthesizes recent research and developments in the application of AI agents across core financial domains. Specifically, it covers the deployment of agent-based AI in algorithmic trading, fraud detection, credit risk assessment, robo-advisory, and regulatory compliance (RegTech). The review focuses on advanced agent-based methodologies, including reinforcement learning, multi-agent systems, and autonomous decision-making frameworks, particularly those leveraging large language models (LLMs), contrasting these with traditional AI or purely… More >

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