IEEE Intelligent Systems is a bimonthly publication of the IEEE Computer Society that provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product.

IEEE Intelligent Systems emphasizes current practice and experience and promising new ideas that will likely see use in the near future. We welcome articles on topics across the spectrum of related work. Example topics include

    Knowledge-based systems
    Intelligent software agents
    Natural language processing
    Knowledge management
    Machine learning
    Data mining
    Adaptive and intelligent robotics
    The Semantic Web
    Social issues relevant to intelligent systems

Special Issue on AI for Health: Challenges and Opportunities
Submission Date: 2022-02-25

Healthcare is a societal need and a huge part of our lives, both personal and professional. Today, health spending accounts for 17.7% of the Gross Domestic Product (GDP) of the USA. Indeed, the gross output of the US healthcare and social assistance industry has increased from $870 billion in 1998 to over $2.5 trillion in 2018. Furthermore, there are new challenges such as new and evolving diseases (e.g., antibiotic-resistant bacteria), evolving situations (e.g., COVID-19 pandemic), and evolving behavior (e.g., anti-vaxxer movement, sedentary lifestyle, opioid crises) that require constant innovation in therapeutic treatments, drug discovery, and other aspects.

There is immense potential for transformative changes in the health and biomedical research community through the adoption of new technologies such as IoT devices, cyber-physical systems, mobile and edge/cloud computing, social networks, and artificial intelligence/machine learning (AI/ML). Together, the use of these technologies and platforms can help us to realize the dream of personalized health and preventive services. However, the burgeoning data-intensive, hyper-connected system of interacting technologies that store, manage, exchange, combine, and utilize sensitive data can be vulnerable to malicious use. Altogether, the use of intelligent computing technologies and systems, while transformational, brings a plethora of security, privacy, trust, and ethical challenges that are unique to health and biomedical research.

This special issue aims to develop a comprehensive vision and gather recent advances in ensuring security, privacy, and ethics in intelligent systems and their applications to health and biomedical research. The special issue will feature novel research on several areas of intelligent systems and data frameworks, including wearables and connected devices, big data analytics and AI/ML technologies in health and biomedical informatics, and the use of real-time multi-modal data for health applications. Besides these, the special issue will focus on research work with compelling results from real-world case studies and successes/failures in emerging applications to health and biomedical research. The contributions should address, but are not limited to, the following research issues/topics, with a specific focus on application in health and biomedical informatics:

- Big data analytics and AI/ML in health and biomedical informatics Adversarial ML Ethics and societal aspects of big data analytics and inequities in care Ethics of autonomous AI systems for health Bias, replicability, and provenance of analytics workflows Issues and concerns with use of open-source tools and technologies Healthcare as a service
- Real-time multi-modal data Personalized medical treatment Life-cycle issues for data Acquisition, integration, and sharing of multimedia data Data collection bias and data quality
- Wearables and connected devices Ownership of data Privacy agreements and data authorization Firmware security for legacy devices Standardization and decommissioning Life-cycle issues for devices
- Information flow and data sharing in health and biomedical informatics Privacy, accountability, and availability Information authenticity and provenance Workflow security