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Naslov:Applicability assessment of technologies for predictive and prescriptive analytics of nephrology big data
Avtorji:ID Stojanov, Riste (Avtor)
ID Jovanovik, Milos (Avtor)
ID Gramatikov, Sasho (Avtor)
ID Vasileska, Ivona (Avtor)
ID Eftimov, Tome, Institut "Jožef Stefan" (Avtor)
ID Trajanov, Dimitar (Avtor), et al.
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202400135
 
.pdf PDF - Predstavitvena datoteka, prenos (1,06 MB)
MD5: A19EA47FD9AA8BC87BDCCFB0BF28ABFE
 
Jezik:Angleški jezik
Tipologija:1.02 - Pregledni znanstveni članek
Organizacija:Logo IJS - Institut Jožef Stefan
Povzetek: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.
Ključne besede:large language models, data standardization
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:18.08.2024
Datum sprejetja članka:25.04.2025
Datum objave:27.05.2025
Založnik:Wiley
Leto izida:2025
Št. strani:str. 1-16
Številčenje:Vol. 25, iss. 9/10
Izvor:ZDA
PID:20.500.12556/DiRROS-22563 Novo okno
UDK:004.6
ISSN pri članku:1615-9861
DOI:10.1002/pmic.202400135 Novo okno
COBISS.SI-ID:238301187 Novo okno
Avtorske pravice:© 2025 The Author(s).
Opomba:Nasl. z nasl. zaslona; Soavtorja iz Slovenije: Ivona Vasileska, Tome Eftimov; Opis vira z dne 4. 6. 2025;
Datum objave v DiRROS:04.06.2025
Število ogledov:529
Število prenosov:259
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Proteomics
Skrajšan naslov:Proteomics
Založnik:Wiley
ISSN:1615-9861
COBISS.SI-ID:515039513 Novo okno

Gradivo je financirano iz projekta

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Financer:COST (European Cooperation in Science and Technology)
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Akronim:KG-Enrich

Financer:EC - European Commission
Program financ.:HE
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Program financ.:HE
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Številka projekta:322900939

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Številka projekta:403224013

Financer:Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
Številka projekta:445703531

Financer:EC - European Commission
Program financ.:H2020
Številka projekta:722609
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Akronim:INTRICARE

Financer:EC - European Commission
Program financ.:H2020
Številka projekta:764474
Naslov:Combatting the CardioRenal Syndrome: towards an integrative Analysis to reduce cardiovascular burden in chronic kidney disease
Akronim:CaReSyAn

Licence

Licenca:CC BY-NC 4.0, Creative Commons Priznanje avtorstva-Nekomercialno 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc/4.0/deed.sl
Opis:Licenca Creative Commons, ki prepoveduje komercialno uporabo, vendar uporabniki ne rabijo upravljati materialnih avtorskih pravic na izpeljanih delih z enako licenco.
Začetek licenciranja:27.05.2025
Vezano na:VoR

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:veliki jezikovni modeli, standardizacija podatkov


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