AIMC Topic: Kidney Diseases

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Identification of glomerulosclerosis using IBM Watson and shallow neural networks.

Journal of nephrology Jan 18, 2022
BACKGROUND: Advanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems levera...
Humans Kidney Kidney Diseases Kidney Glomerulus Sclerosis Neural Networks, Computer Artificial Intelligence Female Male
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Artificial Intelligence Assessment of Renal Scarring (AIRS Study).

Kidney360 Nov 11, 2021
BACKGROUND: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans.
Retrospective Studies Humans Artificial Intelligence Kidney Diseases Prospective Studies Cicatrix
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Deep learning-based transformation of H&E stained tissues into special stains.

Nature communications Aug 12, 2021
Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstra...
Reference Standards Biopsy, Large-Core Needle Pathology, Clinical Kidney Diseases Diagnosis, Differential Algorithms Coloring Agents Diagnosis, Computer-Assisted Humans Reproducibility of Results Deep Learning Sensitivity and Specificity Staining and Labeling Kidney
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Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.

The American journal of pathology May 23, 2021
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA ...
Biopsy Fibrosis Image Interpretation, Computer-Assisted Child, Preschool Child Kidney Diseases Young Adult Adult Male Middle Aged Infant Deep Learning Adolescent Female Infant, Newborn Aged Aged, 80 and over Humans
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Development and Validation of a Deep Learning Model to Quantify Interstitial Fibrosis and Tubular Atrophy From Kidney Ultrasonography Images.

JAMA network open May 3, 2021
IMPORTANCE: Interstitial fibrosis and tubular atrophy (IFTA) is a strong indicator of decline in kidney function and is measured using histopathological assessment of kidney biopsy core. At present, a noninvasive test to assess IFTA is not available.
Humans Male Middle Aged Deep Learning Ultrasonography Algorithms Female Adult Image Interpretation, Computer-Assisted Practice Guidelines as Topic Chicago Kidney Diseases Biopsy Fibrosis
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Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Histopathology Mar 8, 2021
Whole slide imaging, which is an important technique in the field of digital pathology, has recently been the subject of increased interest and avenues for utilisation, and with more widespread whole slide image (WSI) utilisation, there will also be ...
Kidney Diseases Allografts Humans Machine Learning Artificial Intelligence Kidney Transplantation Image Processing, Computer-Assisted Kidney
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Deep learning for the classification of medical kidney disease: a pilot study for electron microscopy.

Ultrastructural pathology Feb 14, 2021
Artificial intelligence (AI) is a new frontier and often enigmatic for medical professionals. Cloud computing could open up the field of computer vision to a wider medical audience and deep learning on the cloud allows one to design, develop, train a...
Kidney Diseases Microscopy, Electron Humans Artificial Intelligence Deep Learning Pilot Projects
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Reducing scan time of paediatric Tc-DMSA SPECT via deep learning.

Clinical radiology Dec 16, 2020
AIM: To investigate the feasibility of reducing the scan time of paediatric technetium 99m (Tc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.
Deep Learning Adolescent Time Factors Child, Preschool Child Feasibility Studies Female Kidney Tomography, Emission-Computed, Single-Photon Sensitivity and Specificity Kidney Diseases Technetium Tc 99m Dimercaptosuccinic Acid Male Infant Humans Retrospective Studies
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Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN Nov 5, 2020
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...
Periodic Acid Deep Learning Image Processing, Computer-Assisted Mice Kidney Neural Networks, Computer Animals Algorithms Male Kidney Glomerulus Disease Models, Animal Reproducibility of Results Diagnosis, Computer-Assisted Translational Research, Biomedical Mice, Inbred C57BL Schiff Bases Kidney Diseases Pattern Recognition, Automated
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Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency.

AJR. American journal of roentgenology Sep 22, 2020
The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. A systematic literature search was conducted...
Artificial Intelligence Reproducibility of Results Humans Models, Theoretical Kidney Diseases
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