Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

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...

Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

Imaging Studies IV: Magnetic Resonance Imaging

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

You might also read

Related Articles

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

Sort by

Same author

AI-Assisted Fracture Detection in Orthopedic and Trauma Imaging: Where It Works, Where It Fails, and Principles for Safe Clinical Deployment.

Diagnostics (Basel, Switzerland)·2026

Same author

Image Quality Assessment Methods in Clinical Diagnostic Imaging: Overview of Current Technical Perspectives.

Diagnostics (Basel, Switzerland)·2026

Same author

Artificial Intelligence for RECIST-Based Radiologic Treatment Response Assessment in Solid Tumors: A Systematic Review of Imaging- and Report-Derived Approaches.

Cancers·2026

Same author

Will AI Replace Physicians in the Near Future? AI Adoption Barriers in Medicine.

Diagnostics (Basel, Switzerland)·2026

Same author

Radiomics as a Decision Support Tool for Detecting Occult Periapical Lesions on Intraoral Radiographs.

Journal of clinical medicine·2026

Same author

Chest X-Ray as a Screening Tool for Aortic Arch Dilation: CT-Based Evaluation of Reliability.

Diagnostics (Basel, Switzerland)·2025

Search research articles

Related Experiment Video

Updated: Sep 18, 2025

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

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

Published on: July 11, 2025

AI in Medical Imaging and Image Processing.

Karolina Nurzynska¹, Michał Strzelecki², Adam Piórkowski³

¹Algorithmics and Software Division, Silesian University of Technology, 44-100 Gliwice, Poland.

Journal of Clinical Medicine

|June 26, 2025

Summary

This summary is machine-generated.

Artificial intelligence (AI) enables automated data analysis, yielding consistent results. AI assists specialists and less experienced personnel in achieving high-quality outcomes.

More Related Videos

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Related Experiment Videos

Last Updated: Sep 18, 2025

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

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

Published on: July 11, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Area of Science:

Computer Science
Data Science
Medical Informatics

Background:

Artificial intelligence (AI) methods have advanced significantly.
AI is increasingly applicable to automatic data analysis tasks.

Discussion:

AI provides standardized and reproducible results.
AI performance is comparable to that of highly skilled specialists.
AI tools can assist less experienced personnel, enhancing their capabilities.

Key Insights:

AI facilitates consistent and reliable data analysis.
AI bridges the skill gap, democratizing access to expert-level analysis.
The integration of AI in data analysis promises improved efficiency and accuracy.

Outlook:

Future applications of AI in data analysis are expected to expand.
Continued development in AI will further enhance its utility in scientific research.
AI holds the potential to revolutionize data interpretation across various fields.