Eva K. Lee, Georgia Institute of Technology

Ariela Sofer, George Mason University

Optimization has long been a cornerstone for advancement of various industrial, government, and military applications. In recent years, it has become increasingly important in advancing research and development related to medical and biological applications. Complexity of medical devices and delivery systems demands solutions to complex decision problems; and biological and clinical applications provide rich, sometimes overwhelming, sources of data upon which challenging optimization problems must be formulated and solved. Such challenges stimulate partnerships between members of the mathematical programming community and biologists, clinicians, public health officials, and others. These partnerships provide excellent opportunities to push the frontier of theoretical and computational optimization while solving important problems that benefit society and mankind.

To highlight and support the role of optimization and computation in such applications, and to disseminate advances to the broad research community in a timely manner, the Annals of Operations Research: Operations Research in Medicine special section was established in 2000. Each volume is devoted to presenting state-of-the-art research results in this dynamic and exciting area. We seek original, high quality contributions that investigate theoretical or methodological work on models and algorithms involving continuous linear and nonlinear optimization, integer programming, combinatorial optimization and stochastic approaches applied to medical and biological applications.

Manuscripts must be original, previously unpublished, and not currently under review in other journals. Each manuscript will be subjected to peer review according to the standard of Annals of Operations Research.

Potential topics

• Disease modeling
• Medical diagnosis
• Treatment planning
• Biological and medical imaging
• Epidemiology
• Molecular biology
• Continuous linear and nonlinear optimization applied to medical and biological applications
• Integer programming applied to medical and biological applications
• Combinatorial optimization applied to medical and biological applications
• Stochastic approaches applied to medical and biological applications

Timeline

• Invalid DateTime: Submission deadline

Timeline

• January 1, 2027: Submission deadline

This Journal of Enterprise Information Management Special Issue seeks to understand Agentic Artificial Intelligence and Generative AI (GenAI) in healthcare, and how these technologies impact the governance, strategy, and value creation of healthcare organizations. In technological innovation, digital technologies are reconfiguring value creation processes and prompting organizations to develop new adaptive strategies. In healthcare, this transformation is driving the adoption of innovative solutions to enhance value for stakeholders while supporting more personalised, predictive, and preventive models of care. AI and GenAI are emerging as strategic levers for optimising resource allocation, supporting new care delivery paradigms, and accelerating research and development. The rapid emergence of Agentic AI systems introduces a further step in this transformation, with AI technologies moving from reactive tools towards semi-autonomous systems able to plan, coordinate and monitor actions across complex organizations.

Healthcare is a relevant setting for examining how innovation management shapes competitiveness, sustainability, and value-creation capabilities. Recent debate has shifted from a focus on the technical performance of AI systems to broader concerns related to implementation, accountability, trustworthiness, evaluation, and organisational sustainability. This shift is crucial in healthcare, where Agentic AI and GenAI are not merely digital transformation tools, but sociotechnical systems that potentially affect clinical practices, decision-making processes, care coordination, patient-doctor relationships, resource allocation and costs optimization.

AI and GenAI are sociotechnical systems with growing autonomy and interactive capabilities, thereby raising new questions around trust, responsibility, human oversight, and governance. As such, they pose a significant challenge to enterprise information management, affecting processes, data, professional roles, compliance, procurement, and monitoring systems.

The deployment of Agentic AI and GenAI occurs in high-risk, highly regulated, data and human-intensive settings. Healthcare organizations must balance innovation with patient safety, care quality, ethical and regulatory issues, data protection and human oversight preservation. Errors, biases and unclear accountability may affect patients, professionals and healthcare ecosystems.

This Special Issue seeks theoretical and empirical contributions examining how health systems, healthcare organizations, and providers develop capabilities, governance structures, and evaluation practices to move from experimentation to technology adoption and integration. Particular attention will be given to agentic workflow integration, responsible value creation, data governance, clinical and managerial accountability, human oversight, professional role reconfiguration, patient-doctor relationship, organisational capabilities and compliance with existing regulatory frameworks.

By focusing on healthcare as the empirical and theoretical context, this Special Issue aims to generate new insights into how Agentic and GenAI systems can be responsibly embedded in healthcare organizations while balancing innovation, safety, equity, trust, regulatory compliance and measurable clinical, organisational, and societal value.

Potential topics

• How are GenAI and Agentic AI reshaping clinical, administrative, and managerial workflows in healthcare organizations?
• How do healthcare organizations govern Agentic AI systems across care pathways?
• What organizational capabilities are needed to move from experimental GenAI applications to integrated and scalable Agentic healthcare systems?
• How can healthcare organizations ensure meaningful human oversight when AI systems become more autonomous, proactive, and embedded in clinical or administrative processes?
• How do GenAI and agentic AI create, capture, or potentially destroy value for different healthcare stakeholders?
• How do Agentic and GenAI systems transform healthcare knowledge management?
• How can healthcare organizations evaluate and measure the clinical, organizational, economic, ethical, and societal value generated by GenAI and Agentic AI adoption?
• What governance mechanisms are needed to ensure accountability, transparency and regulatory compliance in AI-enabled healthcare organizations?
• How do GenAI and Agentic AI affect decision-making processes within healthcare organizations?
• How can healthcare organizations manage risks related to automation bias, inequitable outcomes and over-reliance on AI?
• How do agentic AI and GenAI support healthcare system sustainability?

Timeline

• January 1, 2027: Opening date for manuscript submissions
• June 30, 2027: Closing date for manuscript submissions