Application of Artificial Intelligence in the Management of Patients with Renal Dysfunction
Renal failure is a common condition that affects millions of people worldwide. The diagnosis and treatment of this condition can be challenging due to its complexity and heterogeneity. In recent years, advances in machine learning and artificial intelligence have opened up new opportunities for exploring renal failure diagnosis and treatment. Our special edition delves into the latest research and techniques in applying machine learning and artificial intelligence to multi-omics data analysis for the diagnosis and treatment of renal failure. We explore the use of deep learning algorithms to identify patterns in large-scale, high-dimensional data sets obtained from a variety of sources such as genomics, transcriptomics, proteomics, and metabolomics. These techniques facilitate the classification of renal failure patients into subgroups based on their biological characteristics and clinical traits, and can help to identify potential drug targets for personalized treatment. Our special issue also features articles that highlight the challenges and opportunities of translating these new technologies in real-world clinical settings. We examine the potential of integrating machine learning and artificial intelligence with electronic health records (EHR) to improve clinical decision-making, patient management, and healthcare outcomes in renal failure. Overall, this special issue presents cutting-edge research and insights on the intersection of machine learning, artificial intelligence, and multi-omics data analysis in the diagnosis and treatment of renal failure. With contributions from leading experts in the field, the journal provides a unique and comprehensive overview of the latest advancements in this exciting area of research.
Edited by
Dr. Zhongheng Zhang, MD(Sir Run Run Shaw Hospital, Zhejiang University School of Medicine)