Call for Papers |
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Dear Colleagues,
the (Springer) Neural Computing and Applications journal is currently running a Special Issue entitled “Explainable Artificial Intelligence for Medical Applications”, which is open for submissions. https://www.springer.com/journal/521/updates/25990308 The official submission deadline for this special issue is on January 31, 2024. Please, find below the call for papers. ========================================================= CALL FOR PAPERS Neural Computing and Applications (Springer) Impact Factor: 6.0 (JCR 2022) Special Issue on Explainable Artificial Intelligence for Medical Applications ========================================================= AIMS, SCOPE AND OBJECTIVE Explainable Artificial Intelligence (XAI) has emerged as a crucial aspect in ensuring responsible and trustworthy deployment of machine intelligence systems, and its significance in the healthcare domain has been gaining increasing attention in recent years. With the growing use of machine learning algorithms and AI systems in the medical field, XAI can provide valuable and even life-saving solutions. However, this also presents new ethical and legal questions that need to be thoroughly addressed. The need for explainability and interpretability of AI systems is crucial in healthcare, especially in critical applications. Healthcare providers and patients must be able to understand and trust the decision-making processes of AI-driven systems. XAI offers transparency and clear explanations of how these systems make decisions, providing insights into the underlying reasoning and justifications. This helps build trust and confidence in the use of AI in healthcare, as it allows for a better understanding of the outcomes and actions taken by the systems. In light of these considerations, this topical collection aims to gather innovative research papers, encompassing both theoretical and experimental studies, that focus on the latest advancements in XAI for trustworthy machine intelligence in healthcare. The goal is to promote the development of XAI techniques tailored specifically for healthcare applications and highlight the challenges that need to be overcome to ensure AI's responsible and ethical use in healthcare. By bringing together cutting-edge research in XAI for healthcare, this topical collection aims to foster a deeper understanding of the importance of explainability and interpretability in the context of AI-driven healthcare systems. It also seeks to promote discussions on the ethical, legal, and societal implications of using AI in healthcare and identify potential solutions and best practices for building trustworthy machine intelligence in healthcare settings. The ultimate goal is to ensure that the deployment of AI in healthcare is responsible, transparent, and accountable, and that it ultimately benefits patients, healthcare providers, and society as a whole. ========================================================= TOPICS OF INTEREST Topics of interest of the topical collection include, but are not limited to, the following: - XAI methods for medical decision-making support systems - Interpreting deep learning models in healthcare applications - Explanation methods for medical imaging analysis - Ethical and legal issues in XAI in healthcare - Human-centered XAI design for healthcare applications - Evaluating the effectiveness and trustworthiness of XAI in healthcare - XAI for personalized medicine - Transparent decision-making processes - Real-world deployment and evaluation of XAI in healthcare ========================================================= GUEST EDITORS Agostino Forestiero – ICAR - CNR, Italy – [email protected] Gianni Costa – ICAR - CNR, Italy - [email protected] Riccardo Ortale – ICAR - CNR, Italy – [email protected] ========================================================= KEY DATES Manuscript submission deadline: January 31, 2024 ========================================================= FURTHER INFORMATION Special-issue web-site: https://www.springer.com/journal/521/updates/25990308 |
Credits and Sources |
| [1] Neural Computing and Applications 2023 : Special Issue on Explainable Artificial Intelligence for Medical Applications |
