Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Imaging Studies I: Kidney, Ureter, and Bladder Studies01:28

Imaging Studies I: Kidney, Ureter, and Bladder Studies

44
Kidney, Ureter, and Bladder (KUB) StudiesKidney, Ureter, and Bladder (KUB) studies are standard diagnostic imaging procedures used to assess the anatomy of the urinary system. They are commonly utilized for patients experiencing abdominal pain or urinary symptoms. By using a simple X-ray of the abdomen, KUB studies can reveal structural and pathological abnormalities within the kidneys, ureters, and bladder. These studies are particularly valuable in diagnosing kidney stones, urinary...
44
Classification of Illness01:17

Classification of Illness

8.0K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.0K
Chronic Kidney Disease II: Clinical Manifestations01:24

Chronic Kidney Disease II: Clinical Manifestations

104
Chronic Kidney Disease (CKD) progressively impairs multiple body systems due to the accumulation of uremic toxins, which disrupt cellular functions across various organs.Neurologic symptomsNeurologic symptoms often arise early in CKD, as uremic toxin buildup drives changes in cognitive and motor functions. Patients frequently experience fatigue, headache, confusion, difficulty concentrating, and, in severe cases, seizures. Peripheral neuropathy commonly manifests as burning sensations in the...
104
Chronic Kidney Disease I: Introduction01:25

Chronic Kidney Disease I: Introduction

76
Chronic Kidney Disease (CKD) arises when the kidneys progressively lose their ability to function, ultimately leading to end-stage renal disease. At this advanced stage, the kidneys can no longer filter waste or maintain essential body functions, requiring renal replacement therapy (RRT) through dialysis or a kidney transplant for survival.Early-stage chronic kidney disease and detection challengesIn CKD's early stages, symptoms often remain absent because healthy nephrons compensate for...
76
Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

59
Accurate diagnosis and effective prevention are critical in managing Acute Kidney Injury (AKI), which is linked to high mortality rates ranging from 10% to 80%. Timely recognition of at-risk patients and careful monitoring can significantly reduce the likelihood of kidney damage.Diagnostic Assessments:The diagnostic process starts with a comprehensive medical history to identify prerenal, intrarenal, and postrenal causes.Prerenal causes, such as dehydration, hypotension, or blood loss, should...
59
External Anatomy of the Kidney01:21

External Anatomy of the Kidney

1.7K
The kidneys are a pair of bean-shaped organs in the human body that play a critical role in maintaining overall health. They filter out waste products from the blood, regulate blood pressure, maintain electrolyte balance, and stimulate the production of red blood cells.
The kidneys are located in the retroperitoneal space on either side of the vertebral column, protected posteriorly by the 11th and 12th ribs. The right kidney sits slightly lower than the left owing to the presence of the liver...
1.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Antioxidant Therapy Reverses Sound Stress-Induced Opioid Resistance in a Mouse Model of Mechanical Allodynia.

Journal of pain research·2026
Same author

A Case of Successful Stent Retriever Angioplasty Using the Tigertriever for Acute M1 Segment Occlusion of the Middle Cerebral Artery due to Atherosclerotic Disease.

Journal of neuroendovascular therapy·2026
Same author

Tree-Structured Orthonormal Decomposition of the Aitchison Simplex.

ArXiv·2026
Same author

A Nomogram Predicts the Need for Internal Iliac Vein Dissection During Renal Transplantation: A Multicenter Collaborative Study.

Transplantation proceedings·2026
Same author

SIRT7 Inhibits Adipose Tissue Browning Through Deacetylation of PPARγ2 at K382.

Cells·2026
Same author

Early Clinical Experience with Carotid Artery Stenting for Internal Carotid Artery Stenosis Using the Protcas GW Protection System.

Journal of neuroendovascular therapy·2026

Related Experiment Video

Updated: Sep 17, 2025

Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
07:35

Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring

Published on: June 23, 2015

11.6K

Multiple instance learning using pathology foundation models effectively predicts kidney disease diagnosis and

Yu Kurata, Imari Mimura, Satoshi Kodera

    Medrxiv : the Preprint Server for Health Sciences
    |June 30, 2025
    PubMed
    Summary

    Pathology foundation models combined with multiple instance learning (MIL) show strong diagnostic performance in kidney pathology. These AI models accurately identify disease features and outperform traditional methods in external validation for renal pathology analysis.

    More Related Videos

    Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
    05:33

    Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

    Published on: July 11, 2025

    269
    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
    09:16

    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

    Published on: June 18, 2020

    7.0K

    Related Experiment Videos

    Last Updated: Sep 17, 2025

    Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
    07:35

    Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring

    Published on: June 23, 2015

    11.6K
    Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
    05:33

    Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

    Published on: July 11, 2025

    269
    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
    09:16

    Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

    Published on: June 18, 2020

    7.0K

    Area of Science:

    • Renal pathology
    • Computational pathology
    • Artificial intelligence in medicine

    Background:

    • Histological analysis of kidney biopsies is essential for diagnosing kidney diseases and predicting outcomes.
    • Pathology foundation models, pretrained on large datasets, offer promising performance for downstream tasks.
    • Integrating these models with multiple instance learning (MIL) for kidney pathology analysis warrants investigation.

    Purpose of the Study:

    • To evaluate the utility of pathology foundation models combined with MIL for kidney pathology analysis.
    • To compare the diagnostic performance of foundation models against a traditional ResNet50 model.
    • To assess the models' ability to generalize to external datasets and predict clinical outcomes.

    Main Methods:

    • Utilized 242 H&E-stained whole slide images (WSIs) from KPMP and JP-AID for internal validation.
    • Included healthy controls, acute interstitial nephritis, and diabetic kidney disease (DKD) cases.
    • Performed external validation on 83 WSIs from the University of Tokyo Hospital (UT dataset).
    • Employed pretrained pathology foundation models as patch encoders, comparing them with ImageNet-pretrained ResNet50.

    Main Results:

    • Foundation models significantly outperformed ResNet50 in internal validation (AUROC > 0.980).
    • In external validation, foundation models maintained high performance (AUROC > 0.800) while ResNet50 performance dropped (AUROC = 0.768).
    • Attention heatmaps confirmed foundation models recognized diagnostically relevant structures.
    • Foundation models also outperformed ResNet50 in predicting severe proteinuria in DKD cases.

    Conclusions:

    • Pathology foundation models integrated with MIL achieve robust diagnostic performance in renal pathology.
    • These models demonstrate strong generalization capabilities, even with limited training data.
    • The findings highlight the potential of foundation models for real-world clinical applications in kidney disease diagnosis.