Bringing Precision Medicine into the Clinical Practice: The Role of Explainable Artificial Intelligence and Interpretable Models
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 1076
Special Issue Editors
Interests: medical image analysis; deep learning; radiomics; pathomics; clinical decision support; explainable artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Precision Medicine paves the way to tailor disease prevention and treatment in a specialized manner for each patient, leveraging on high-throughput patient data, encompassing clinical, imaging, and multi-omics features, among the others. Artificial Intelligence (AI) techniques have a huge impact on the handling of this incredible quantity and variety of data for predicting diagnosis, prognosis, or treatment. Nevertheless, Clinical Decision Support Systems (CDSS) based on AI are difficult to implement in the clinical routine, since AI systems are seen as black boxes by both physicians and patients. To further complicate this issue, the latest developments of CDSS do not concern single-type data analysis but involve multimodal fusion from multiple sources with a high heterogeneity. Interpretable Models, such as decision trees and linear regressors or classifiers, whose decisions can be easily understood by the stakeholders involved, are often too simple to effectively handle intricate medical data analysis tasks. Nevertheless, efforts in Feature Reduction techniques can help in individuating a small subset of relevant characteristics that can act as a simplified diagnostic, prognostic, or therapeutic signature. In recent years, Explainable Artificial Intelligence (XAI) has established as a fundamental theme in the research involving applications of AI in medicine, offering the possibility to unveil the mechanisms behind the decision-making process of those complex automated systems. Furthermore, novel applications of XAI are emerging, as those related to provide time-dependent explanations for survival models, enabling new frontiers of analysis to the practitioners. Hence, this special issue investigates the potential offered by XAI and Interpretable Models in enabling the adoption of Precision Medicine into clinical practice. Methodological articles concerning algorithmic developments, as well as impactful applications that leverage on existing methods, can be submitted to this Special Issue. Research areas may include (but are not limited to) the following:
- Explainable CDSS
- XAI for Medical Imaging
- Clinical Translation through XAI
- Time-dependent XAI
- Multimodal Data Analysis
- Interpretable Models
- Feature Reduction
- Radiomics
- Pathomics
- Bioinformatics
We look forward to receiving your contributions.
Dr. Nicola Altini
Dr. Gian Maria Zaccaria
Guest Editors
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Keywords
- precision medicine
- clinical practice
- explainable artificial intelligence
- interpretable models
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