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

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.3K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.3K
Chronic Kidney Disease III: Interprofessional Care01:28

Chronic Kidney Disease III: Interprofessional Care

494
Chronic kidney disease (CKD) requires collaborative and comprehensive management. CKD progresses through stages and can lead to end-stage kidney disease (ESKD) if untreated. Interprofessional collaboration and patient education are crucial, enabling patients to manage their health and improve their quality of life.Diagnostic approach for chronic kidney diseaseThe diagnosis of CKD primarily focuses on the glomerular filtration rate (GFR), which assesses kidney function by measuring how well...
494
Acute Kidney Injury V: Interprofessional Care01:20

Acute Kidney Injury V: Interprofessional Care

370
Acute Kidney Injury (AKI) requires a collaborative healthcare approach to restore renal function and prevent complications. Essential management strategies involve monitoring fluid and electrolyte balance, adjusting medications, initiating dialysis when necessary, and providing nutritional support.Fluid and Electrolyte ManagementFluid Monitoring: Regularly monitoring body weight, central venous pressure, and urine output helps detect fluid imbalances early. Patient intake and output are...
370
Chronic Kidney Disease I: Introduction01:25

Chronic Kidney Disease I: Introduction

798
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...
798
Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

357
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...
357
Nursing Clinical Information System01:27

Nursing Clinical Information System

1.3K
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
1.3K

You might also read

Related Articles

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

Sort by
Same author

"Check Symptoms & Get Care": Mount Sinai's AI Triage Solution.

NEJM catalyst innovations in care delivery·2026
Same author

Beyond Diffusion and Convection: Is Adsorption the Third Dimension of Dialysis?

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026
Same author

Lewy pathology largely absent in prefrontal cortices of Parkinson's disease patients undergoing deep brain stimulation.

NPJ Parkinson's disease·2026
Same author

Artificial Intelligence in Rare Diseases: Workflow-Integrated Precision Kidney Care.

Clinics and practice·2026
Same author

LATAM-AKID registry: an international multicentre, observational study of acute kidney injury requiring dialysis in Latin America.

BMJ open·2026
Same author

Pathophysiology of pregnancy-associated acute kidney injury.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2026

Related Experiment Video

Updated: Feb 19, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

5.4K

Transforming nephrology through artificial intelligence: a state-of-the-art roadmap for clinical integration.

Wisit Cheungpasitporn1, Ambarish Athavale2, Lama Ghazi3

  • 1Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA.

Clinical Kidney Journal
|February 18, 2026
PubMed
Summary

Artificial intelligence (AI) is transforming nephrology for earlier kidney disease detection and personalized care. AI tools are advancing acute kidney injury (AKI), chronic kidney disease (CKD), dialysis, and transplantation, facing implementation challenges.

Keywords:
acute kidney injuryartificial intelligencechronic kidney diseasedialysiskidney transplantation

More Related Videos

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

5.3K
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

1.2K

Related Experiment Videos

Last Updated: Feb 19, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

5.4K
Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

5.3K
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

1.2K

Area of Science:

  • Nephrology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Artificial intelligence (AI), including machine learning, deep learning, and generative AI, is set to revolutionize kidney disease care.
  • AI offers potential for earlier detection, precise risk stratification, and integrated clinical decision support.

Purpose of the Study:

  • To review emerging AI applications across the spectrum of kidney disease: acute kidney injury (AKI), chronic kidney disease (CKD), dialysis, and transplantation.
  • To examine clinical integration, real-world validation, workflow implementation, and translational challenges of AI in nephrology.

Main Methods:

  • Synthesis of state-of-the-art research on AI applications in nephrology.
  • Analysis of AI's role in AKI, CKD, dialysis, and transplantation, considering implementation factors.

Main Results:

  • AI shows promise in AKI prediction, CKD risk stratification, optimizing dialysis, and enhancing transplantation processes.
  • Generative AI and large language models offer new avenues for documentation and patient education.
  • Validated AI tools are emerging, but challenges like data heterogeneity, bias, interpretability, and regulatory hurdles persist.

Conclusions:

  • AI integration in nephrology requires addressing implementation challenges and evolving regulatory frameworks.
  • Multimodal data integration and adaptive AI paradigms will drive precision nephrology.
  • Clinician engagement is crucial for developing, validating, and deploying AI to ensure a personalized, efficient, and equitable future for kidney care.