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

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.1K
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...
5.1K

You might also read

Related Articles

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

Sort by
Same author

Baseline vulnerability over dosimetric precision: reframing late urinary toxicity after prostate stereotactic body radiotherapy.

Translational andrology and urology·2026
Same author

Mind the gap: challenges and future directions for content-based image retrieval in clinical radiology.

Frontiers in radiology·2026
Same author

Global Disparities and Trends in Radiotherapy for Early-Stage Glottic Cancer.

Current oncology (Toronto, Ont.)·2026
Same author

A dual-layer quality assurance approach leveraging dose prediction for efficient review of automated contours of organs at risk in the brain in radiotherapy.

Physics and imaging in radiation oncology·2026
Same author

Therapeutic outcomes of ²²⁵Ac/¹⁷⁷Lu-PSMA combination therapy in advanced metastatic Castration-Resistant prostate cancer: A systematic review and Meta-Analysis.

European journal of nuclear medicine and molecular imaging·2025
Same author

Clinical Outcomes and Safety of Ultra-Low-Dose Radiotherapy for Ocular Adnexal Lymphoma: A Systematic Review.

Cancers·2025

Related Experiment Video

Updated: Jun 20, 2025

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K

Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging.

Aurélie Pahud de Mortanges1, Haozhe Luo2, Shelley Zixin Shu2

  • 1ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland. aurelie.pahuddemortanges@unibe.ch.

NPJ Digital Medicine
|July 22, 2024
PubMed
Summary

Explainable artificial intelligence (XAI) systems are advancing, but clinical usability with complex patient data remains a challenge. This study reviews XAI for multimodal, longitudinal data and proposes an "XAI orchestrator" to aid clinicians.

More Related Videos

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.1K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K

Related Experiment Videos

Last Updated: Jun 20, 2025

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.1K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K

Area of Science:

  • Artificial Intelligence in Medicine
  • Clinical Informatics
  • Data Science

Background:

  • Explainable artificial intelligence (XAI) has rapidly advanced technically.
  • Clinical applicability and usability of XAI systems are under-explored.
  • XAI for multimodal and longitudinal clinical data requires further attention.

Purpose of the Study:

  • To review the clinical perspective of current XAI for multimodal and longitudinal datasets.
  • To identify challenges in applying XAI to complex clinical data.
  • To propose a novel XAI orchestrator concept for clinical workflows.

Main Methods:

  • Literature review focusing on clinical applicability of XAI.
  • Analysis of XAI capabilities for multimodal and longitudinal data.
  • Conceptualization of an XAI orchestrator framework.

Main Results:

  • Current XAI research lacks focus on clinical usability and complex data types.
  • Significant challenges exist in integrating XAI with multimodal and longitudinal clinical data.
  • The proposed XAI orchestrator offers a potential solution for clinical data synopsis and AI interpretation.

Conclusions:

  • Bridging the gap between technical XAI advancements and clinical needs is crucial.
  • Handling multimodal and longitudinal data is essential for effective clinical XAI.
  • The proposed XAI orchestrator, with properties like adaptivity and uncertainty-awareness, could enhance clinical decision-making.