| Title: | Applicability assessment of technologies for predictive and prescriptive analytics of nephrology big data |
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| Authors: | ID Stojanov, Riste (Author)
ID Jovanovik, Milos (Author)
ID Gramatikov, Sasho (Author)
ID Vasileska, Ivona (Author)
ID Eftimov, Tome, Institut "Jožef Stefan" (Author)
ID Trajanov, Dimitar (Author), et al. |
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| Files: |  URL - Source URL, visit https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202400135
 PDF - Presentation file, download (1,06 MB)
MD5: A19EA47FD9AA8BC87BDCCFB0BF28ABFE
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| Language: | English |
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| Typology: | 1.02 - Review Article |
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| Organization: |  IJS - Jožef Stefan Institute
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| Abstract: | The integration of big data into nephrology research will open new avenues for analyzing and understanding complex biological datasets, driving advances in personalized management of kidney diseases. This paper describes the multifaceted challenges and opportunities by incorporating big data in nephrology, emphasizing the importance of data standardization, advanced storage solutions, and advanced analytical methods. We discuss the role of data science workflows, including data collection, preprocessing, integration, and analysis, in facilitating comprehensive insights into disease mechanisms and patient outcomes. Furthermore, we highlight predictive and prescriptive analytics, as well as the application of large language models (LLMs) in improving clinical decision-making and enhancing the accuracy of disease predictions. The use of high-performance computing (HPC) is also examined, showcasing its role in processing large-scale datasets and accelerating machine learning algorithms. Through this exploration, we aim to provide a comprehensive overview of the current state and future directions of big data analytics in nephrology, with a focus on enhancing patient care and advancing medical research. |
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| Keywords: | large language models, data standardization |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 18.08.2024 |
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| Article acceptance date: | 25.04.2025 |
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| Publication date: | 27.05.2025 |
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| Publisher: | Wiley |
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| Year of publishing: | 2025 |
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| Number of pages: | str. 1-16 |
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| Numbering: | Vol. 25, iss. 9/10 |
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| Source: | ZDA |
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| PID: | 20.500.12556/DiRROS-22563  |
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| UDC: | 004.6 |
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| ISSN on article: | 1615-9861 |
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| DOI: | 10.1002/pmic.202400135 |
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| COBISS.SI-ID: | 238301187 |
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| Copyright: | © 2025 The Author(s). |
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| Note: | Nasl. z nasl. zaslona;
Soavtorja iz Slovenije: Ivona Vasileska, Tome Eftimov;
Opis vira z dne 4. 6. 2025;
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| Publication date in DiRROS: | 04.06.2025 |
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| Views: | 530 |
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| Downloads: | 259 |
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| Metadata: |    |
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