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

240
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...
240
Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

244
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...
244

You might also read

Related Articles

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

Sort by
Same author

Long-Term Outcomes After Childhood Stroke.

Pediatric reports·2026
Same author

General ability and specific cognitive functions are lower in children with epilepsy after perinatal ischemic stroke.

Frontiers in stroke·2026
Same author

Biallelic variants in CELSR1 cause brain malformations, neurodevelopmental disorders and epilepsy in humans.

Nature communications·2026
Same author

Recurrent de novo variants in the spliceosomal factor CRNKL1 are associated with severe microcephaly and pontocerebellar hypoplasia with seizures.

American journal of human genetics·2025
Same author

Ten-Year Results of Inguinal Hernia Open Mesh Repair.

Journal of abdominal wall surgery : JAWS·2025
Same author

Radiological diagnosis of acute mesenteric ischemia in adult patients: a systematic review and meta-analysis.

Scientific reports·2025

Related Experiment Video

Updated: Jan 10, 2026

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

752

A clinically validated AI framework for kidney cancer detection and characterization.

Bohdan Petryshak1,2,3, Mikhail Iljin2, Alina Denissova2,4

  • 1Institute of Computer Science, Tartu University, Tartu, Estonia.

Communications Medicine
|November 27, 2025
PubMed
Summary
This summary is machine-generated.

BMVision, an AI tool for kidney cancer, significantly reduces radiologist reporting time and improves diagnostic sensitivity for renal lesions. This artificial intelligence solution enhances accuracy and efficiency in cancer diagnostics.

More Related Videos

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
12:22

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers

Published on: January 22, 2013

34.1K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K

Related Experiment Videos

Last Updated: Jan 10, 2026

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

752
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
12:22

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers

Published on: January 22, 2013

34.1K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K

Area of Science:

  • Radiology
  • Artificial Intelligence
  • Oncology

Background:

  • Renal cell carcinoma is a common urinary tract cancer diagnosed via CT scans.
  • Increasing demand for radiology services strains timely and accurate cancer diagnosis.
  • Automated tools can enhance radiologist efficiency and diagnostic accuracy.

Purpose of the Study:

  • To develop and evaluate BMVision, a deep learning tool for kidney cancer detection and characterization.
  • To assess the impact of AI assistance on radiologist diagnostic performance and workflow efficiency.

Main Methods:

  • BMVision, a deep learning tool with a web-based viewer, was developed.
  • A two-stage retrospective reader study involved six radiologists reviewing 200 scans.
  • AI-assisted and unaided workflows were compared for diagnostic sensitivity, lesion measurement, reporting efficiency, and inter-radiologist agreement.

Main Results:

  • BMVision reduced radiologist reporting time by an average of 33% (up to 52%).
  • The tool improved sensitivity for detecting benign renal lesions from 79.9% to 86.3%.
  • BMVision led to a significant increase in inter-radiologist agreement and provided structured auto-generated reports.

Conclusions:

  • BMVision is the first clinically validated commercial AI tool for kidney cancer detection and characterization.
  • The tool has the potential to enhance patient care by improving diagnostic accuracy and reporting efficiency.
  • BMVision can help radiologists manage the growing demand for high-quality cancer diagnostics.