The use of artificial intelligence, numerical algorithms and expert approach in selected nephrology problems

Background: The integration of AI, numerical algorithms, and expert approaches in nephrology shows promise for enhancing patient care. Traditionally, nephrology relied on clinician expertise, but the growing volume of data requires innovative methods. AI, fueled by vast datasets, can uncover patterns and improve diagnostic accuracy and treatment optimization. Numerical algorithms enable computational modeling of renal physiology and disease progression, aiding in treatment prediction and optimization. Expert systems codify nephrologists' knowledge into decision support tools, aiding in diagnosis and treatment selection. Embracing these technologies can revolutionize nephrological practice, improving patient outcomes.Aim of the study: The aim of the research is to review scientific works on the use of artificial intelligence (AI), numerical algorithms, and expert algorithms in diagnosis, decision support and prediction of selected disease states and issues related to nephrology.Material and methods: The study rigorously retrieved relevant publications from esteemed academic databases, Scopus and PubMed, and screened them based on predefined criteria. Through keyword-based searches, it analyzed the intersection of nephrology and artificial intelligence, offering insights into emerging trends and advancements. This approach facilitated a comprehensive exploration of the integration of artificial intelligence in nephrology research, paving the way for future developments in the field.Results: Artificial intelligence in nephrology and medicine uses various technologies such as machine learning, deep learning and natural language processing to improve diagnosis, treatment and patient care. Analyzes clinical, laboratory, imaging and genetic data to accelerate the identification of kidney diseases. By integrating health information systems and research data, artificial intelligence enables pattern recognition, outcome prediction and treatment optimization, ultimately having the potential to permanently improve patient care.Conclusions: Numerical algorithms, artificial intelligence, and expert algorithms show promise in nephrology, improving patient care and research.

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Publication Details

Journal
MEDICAL SCIENCE PULSE
Published
2024-09-30
DOI
https://doi.org/10.5604/01.3001.0054.7674
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
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article

The use of artificial intelligence, numerical algorithms and expert approach in selected nephrology problems

Tomasz Porażko, Szczepan Paszkiel, Dawid Pawuś
MEDICAL SCIENCE PULSE
Insurance, Mortality, Demography, Risk Management
article

The use of artificial intelligence, numerical algorithms and expert approach in selected nephrology problems

Tomasz Porażko, Szczepan Paszkiel, Dawid Pawuś
article en

Abstract

Background: The integration of AI, numerical algorithms, and expert approaches in nephrology shows promise for enhancing patient care. Traditionally, nephrology relied on clinician expertise, but the growing volume of data requires innovative methods. AI, fueled by vast datasets, can uncover patterns and improve diagnostic accuracy and treatment optimization. Numerical algorithms enable computational modeling of renal physiology and disease progression, aiding in treatment prediction and optimization. Expert systems codify nephrologists' knowledge into decision support tools, aiding in diagnosis and treatment selection. Embracing these technologies can revolutionize nephrological practice, improving patient outcomes.Aim of the study: The aim of the research is to review scientific works on the use of artificial intelligence (AI), numerical algorithms, and expert algorithms in diagnosis, decision support and prediction of selected disease states and issues related to nephrology.Material and methods: The study rigorously retrieved relevant publications from esteemed academic databases, Scopus and PubMed, and screened them based on predefined criteria. Through keyword-based searches, it analyzed the intersection of nephrology and artificial intelligence, offering insights into emerging trends and advancements. This approach facilitated a comprehensive exploration of the integration of artificial intelligence in nephrology research, paving the way for future developments in the field.Results: Artificial intelligence in nephrology and medicine uses various technologies such as machine learning, deep learning and natural language processing to improve diagnosis, treatment and patient care. Analyzes clinical, laboratory, imaging and genetic data to accelerate the identification of kidney diseases. By integrating health information systems and research data, artificial intelligence enables pattern recognition, outcome prediction and treatment optimization, ultimately having the potential to permanently improve patient care.Conclusions: Numerical algorithms, artificial intelligence, and expert algorithms show promise in nephrology, improving patient care and research.

MEDICAL SCIENCE PULSEVol. 18(3)
Opole University of Technology (PL), University of Opole (PL)
Openalex Percentile: Top 68%
Insurance, Mortality, Demography, Risk Management
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