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Artificial intelligence in renal pathology: Current status and future

Renal biopsy pathology is an essential gold standard for the diagnosis of most kidney diseases. With the increase in the incidence rate of kidney diseases, the lack of renal pathologists, and an imbalance in their distribution, there is an urgent need for a new renal pathological diagnosis model. Ad...

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Detalles Bibliográficos
Autores principales: Feng, Chunyue, Liu, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113937/
https://www.ncbi.nlm.nih.gov/pubmed/36378066
http://dx.doi.org/10.17305/bjbms.2022.8318
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author Feng, Chunyue
Liu, Fei
author_facet Feng, Chunyue
Liu, Fei
author_sort Feng, Chunyue
collection PubMed
description Renal biopsy pathology is an essential gold standard for the diagnosis of most kidney diseases. With the increase in the incidence rate of kidney diseases, the lack of renal pathologists, and an imbalance in their distribution, there is an urgent need for a new renal pathological diagnosis model. Advances in artificial intelligence (AI) along with the growing digitization of pathology slides for diagnosis are promising approach to meet the demand for more accurate detection, classification, and prediction of the outcome of renal pathology. AI has contributed substantially to a variety of clinical applications, including renal pathology. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being used in multiple areas of pathology. In this narrative review, we first provide a general description of AI methods, and then discuss the current and prospective applications of AI in the field of renal pathology. Both diagnostic and predictive prognostic applications are covered, emphasizing AI in renal pathology images, predictive models, and 3D in renal pathology. Finally, we outline the challenges associated with the implementation of AI platforms in renal pathology and provide our perspective on how these platforms might change in this field.
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spelling pubmed-101139372023-04-20 Artificial intelligence in renal pathology: Current status and future Feng, Chunyue Liu, Fei Biomol Biomed Review Renal biopsy pathology is an essential gold standard for the diagnosis of most kidney diseases. With the increase in the incidence rate of kidney diseases, the lack of renal pathologists, and an imbalance in their distribution, there is an urgent need for a new renal pathological diagnosis model. Advances in artificial intelligence (AI) along with the growing digitization of pathology slides for diagnosis are promising approach to meet the demand for more accurate detection, classification, and prediction of the outcome of renal pathology. AI has contributed substantially to a variety of clinical applications, including renal pathology. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being used in multiple areas of pathology. In this narrative review, we first provide a general description of AI methods, and then discuss the current and prospective applications of AI in the field of renal pathology. Both diagnostic and predictive prognostic applications are covered, emphasizing AI in renal pathology images, predictive models, and 3D in renal pathology. Finally, we outline the challenges associated with the implementation of AI platforms in renal pathology and provide our perspective on how these platforms might change in this field. Association of Basic Medical Sciences of Federation of Bosnia and Herzegovina 2023-04-01 2023-03-16 /pmc/articles/PMC10113937/ /pubmed/36378066 http://dx.doi.org/10.17305/bjbms.2022.8318 Text en © 2022 Feng and Liu. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Feng, Chunyue
Liu, Fei
Artificial intelligence in renal pathology: Current status and future
title Artificial intelligence in renal pathology: Current status and future
title_full Artificial intelligence in renal pathology: Current status and future
title_fullStr Artificial intelligence in renal pathology: Current status and future
title_full_unstemmed Artificial intelligence in renal pathology: Current status and future
title_short Artificial intelligence in renal pathology: Current status and future
title_sort artificial intelligence in renal pathology: current status and future
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113937/
https://www.ncbi.nlm.nih.gov/pubmed/36378066
http://dx.doi.org/10.17305/bjbms.2022.8318
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