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Call for papers - Artificial intelligence in nephrology

Guest Editors:
Miguel Hueso Val: Bellvitge University Hospital, Spain
Alfredo Vellido: Polytechnic University of Catalonia, Spain

Submission Status: Open   |   Submission Deadline: 10 January 2025
 

BMC Nephrology welcomes submissions to a Collection on Artificial intelligence in nephrology.

This Collection gathers research on kidney diseases, from basic science to clinical studies, including bioengineers and data scientists, aiming to present novel strategies of analysis to unravel the causes of renal diseases and improving in personalized therapeutics with the goal of achieving precision medicine. We welcome contributions with focus on the role of artificial intelligence in novel data acquisition, synthesis, and interpretation, in scope with the journal’s aims in the diagnosis and treatment of renal diseases.

New Content ItemThis Collection supports and amplifies research related to SDG 3: Good Health & Wellbeing.

Meet the Guest Editors

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Miguel Hueso Val: Bellvitge University Hospital, Spain

Dr Miguel Huseo Val is a nephrologist in the Dialysis Unit at Bellvitge University Hospital. He is also a member of the Research Group in Nephrology at the Bellvitge Biomedical Research Institute (IDIBELL) and the BigData and Artificial Intelligence group with the Spanish Society of Nephrology.

Dr Hueso Val has wide experience in Genetics and Molecular Biology. He currently leads a lab devoted to immunomodulation and the study of molecular mechanism of vascular injury in patients with chronic kidney disease. In his current research, he focuses on the role of lncRNAs as microRNA "sponges", nanotechnology, and the application of Artificial Intelligence for a personalized Hemodialysis. He also serves as an Editorial Board Member for BMC Nephrology.

Alfredo Vellido: Polytechnic University of Catalonia, Spain

Dr Alfredo Vellido is full professor at the Polytechnic University of Catalonia and coordinator of the Health area at the Intelligent Data Science and Artificial Intelligence Research Center. He has over 25 years of experience in Machine Learning applications in health and (bio)medicine.

Dr Vellido is founding member of the Spanish Society of AI in Biomedicine and chair of the Explainable Machine Learning Task Force at the IEEE-Computational Intelligence Society's Data Mining and Big Data Analytics Technical Committee. He is also a member of the Editorial Boards of PLoS ONE, Neural Processing Letters and Frontiers in Artificial Intelligence, Medicine and Public Health.

About the Collection

BMC Nephrology welcomes submissions to a Collection on Artificial intelligence in nephrology.

Current research trends in nephrology represent the beginning of a new era of cross-disciplinary informational synthesis. With accelerating discoveries in genetics, molecular pathways, biochemical interactions and intercellular communication, new potential therapeutic targets are being introduced at an unprecedented rate. With application of novel methods in translational research and vast accumulation of clinical data, personalized treatment regimens have become central in advancing the quality of care and improving outcomes. Innovations in dialysis and transplant management, artificial kidney development, implementation of early diagnostic and disease prevention strategies are at the forefront of a modern patient-centered approach in nephrology.

The continuous flow of novel and constantly evolving information requires a powerful resource for high-level data synthesis and complex analysis in order to find meaning in a perpetually expanding informational field. Artificial Intelligence (AI) technologies, including Machine Learning (ML) are such resources, application of which in clinical and translational research is gaining momentum. The AI generated data-based knowledge has potential to impact patient management strategies by forming support systems for clinical decisions, improving drug design, risk identification and personalization of treatment. In all possible ways, AI and ML are enabling the emergence of “intelligent nephrology”.

This Collection gathers researchers with interest in kidney diseases from different perspectives, from basic science to clinical settings, including bioengineers and data scientists, aiming to present novel strategies of analysis to unravel the causes of renal diseases and improving in personalized therapeutics with the goal of achieving precision medicine. We encourage contributions with focus on the role of AI in novel data acquisition, synthesis, and interpretation, in scope with the journal’s aims in the diagnosis and treatment of renal diseases.

Image credit: Tom / Stock.adobe.com

  2. Current research in nephrology is increasingly focused on elucidating the complexity inherent in tightly interwoven molecular systems and their correlation with pathology and related therapeutics, including di...

    Authors: Miguel Hueso and Alfredo Vellido
    Citation: BMC Nephrology 2024 25:276
    Content type: Editorial Published on:

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Artificial intelligence in nephrology" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.