BMC Medical Informatics and Decision Making is an open access, peer-reviewed journal that considers articles related to the design, development, implementation, use, and evaluation of...
BMC Medical Informatics and Decision Making is calling for submissions to our Collection on Innovations in decision support systems for personalized medicine.
Decision support systems (DSS) are transforming healthcare by enabling personalized medicine, which tailors treatment plans and clinical decisions to individual patients based on their unique characteristics, including genomic, clinical, and environmental data. This special collection will focus on developments in DSS for personalized medicine, emphasizing their design, implementation, and clinical applications.
Submissions should address challenges and solutions in creating adaptable, interpretable, and efficient DSS capable of integrating diverse data types. This collection aims to bridge the gap between theoretical advances and practical implementations, showcasing the role of DSS in enhancing clinical decision-making, patient outcomes, and healthcare efficiency. We invite submissions on the following topics, but not limited to:
- Personalized treatment pathways using DSS
- Integration of DSS with genomic, proteomic, and pharmacogenomic data
- Real-time clinical decision-making systems for individual patient care
- Machine Learning and Artificial Intelligence in Decision Support Systems
- Explainable Artificial Intelligence (XAI) for Interpretable Clinical Decision-Making
- Wearables and Internet of Things (IoT) Data into Decision Support Systems
- Interoperability Challenges in the Integration of Decision Support Systems
- DSS for rare disease diagnosis and management
- Case studies on successful DSS implementations in personalized medicine
- Ethical and regulatory considerations in personalized DSS development
- Data Privacy and Security in Decision Support Systems
This Collection supports and amplifies research related to SDG 3: Good Health & Well-Being and SDG 16: Peace, Justice and Strong Institutions.
All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.
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Lucía Prieto-Santamaría PhD
Universidad Politécnica de Madrid, Spain.Dr Prieto Santamaría is an Assistant Professor at the Universidad Politécnica de Madrid (UPM) and a researcher at the Medical Data Analytics Laboratory (MEDAL), based at the Center for Biomedical Technology (CTB-UPM). She holds a PhD in Software, Systems, and Computing (2023), awarded with the UPM’s Premio Extraordinario de Doctorado and the CTB’s Premio Francisco del Pozo. Her research focuses on the intersection of artificial intelligence and biomedical sciences, with a particular interest in network medicine, drug repurposing, and medical knowledge representation. At UPM, she teaches undergraduate and graduate courses in data processing, databases, and biomedical data analytics. She has supervised numerous theses and currently co-supervises two doctoral dissertations in biomedical AI, having mentored award-winning student research. -
Rosa Sicilia PhD
Università Campus Bio-Medico, Italy.Dr Sicilia is a Biomedical Engineer and PhD graduate from the University Campus Bio-Medico of Rome, where she currently serves as Assistant Professor (RTDA). Her research focuses on artificial intelligence, machine learning, and multimodal data analysis, with applications in healthcare, including rumor detection on social media, radiomics, and Hospital 4.0 systems. Her work includes 43 publications (454 citations, h-index 12 as of 2025). She co-holds a patent for an AI-enabled subcutaneous insulin delivery device and was part of the winning team in a global medical imaging challenge in 2021. -
Chia-Yu (Emily) Su PhD
National Yang Ming Chiao Tung University, Taiwan.Professor Emily Chia-Yu Su is a researcher and educator in biomedical informatics, artificial intelligence, and computational biology. She is Professor at the Institute of Biomedical Informatics, College of Medicine, National Yang Ming Chiao Tung University, and Adjunct Professor at Taipei Medical University. Her research centers on medical informatics, machine learning, clinical decision support systems, natural language processing, and immunoinformatics. She received her Ph.D. in Bioinformatics from the Taiwan International Graduate Program at Academia Sinica in 2009, an M.S. in Computer Science and Information Engineering from National Taiwan University in 2003, and a B.S. in Information and Computer Education from National Taiwan Normal University in 2001. She completed postdoctoral training at Academia Sinica and served as a visiting scientist at the U.S. National Institutes of Health in 2010. Professor Su began her academic career at Taipei Medical University in 2009, progressing to Associate Professor in 2017 and Professor in 2022, before joining National Yang Ming Chiao Tung University in 2024. She has held joint appointments with the Professional Master Program in Artificial Intelligence in Medicine and the Clinical Big Data Research Center, promoting translation of computational methods into clinical practice. She currently serves as Core Faculty of the Bioinformatics Program at the Taiwan International Graduate Program, Director of the Taiwan Bioinformatics and Systems Biology Society, and Supervisor of the Taiwan Association for Medical Informatics, where she previously served as Director (2021–2025). Professor Su has published more than 100 peer-reviewed articles in leading journals, addressing vaccine impact analysis, COVID-19 modeling, chronic disease management, adverse drug reaction detection, protein function prediction, and AI-driven precision medicine. She is also an active reviewer, conference organizer, and invited speaker, committed to advancing biomedical data science and interdisciplinary education.
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Josip Vrdoljak MD, PhD, MSc
University of Split, Croatia.Dr Josip Vrdoljak MD, PhD, is a post-doctoral researcher in Machine Learning in Medicine at the University of Split School of Medicine, where he leads and contributes to projects that translate advanced AI into day-to-day clinical workflows. He earned his PhD in 2023 with a multicentre study on lymph-node metastasis prediction in breast cancer and has completed an MSc in Artificial Intelligence, adding formal depth in modern deep-learning and NLP methods to his clinical background. His recent research focus is in integrating and evaluating Large Language Models as Decision Support Tools in real world clinical practice.
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