Related Experiment Video
Updated: Jan 19, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
On the promise of artificial intelligence for standardizing radiographic response assessment in gliomas
1UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.
No abstract available in PubMed .
Related Concept Videos
06:37Artificial Intelligence-Based System for Detecting Attention Levels in Students
08:58Artificial Intelligence Approaches to Assessing Primary Cilia
09:11Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
05:33Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
09:29A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
05:49Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

