ReviewPhysical and engineering sciences in medicine2025
Artificial intelligence and its potential integration with the clinical practice of diagnostic imaging medical physicists: a review.
Review in Physical and engineering sciences in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Deep unrolled regularization for limited-angle dual-panel positron emission mammography.Physical and engineering sciences in medicine · 2026Article
- Automated health monitoring system using YOLOv8 for real-time device parameter detection.Physical and engineering sciences in medicine · 2026Article
- Image Quality Optimization in 60 kVp Head-Neck CTA: A Comparative Study of FBP, ClearView, and ClearInfinity Reconstruction Algorithms.Current medical science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current clinical practice in imaging medical physics is concerned with quality assurance, image processing and analysis, radiation dosimetry, risk assessment and radiation protection, and in-house training and research. Physicist workloads are projected to increase as medical imaging technologies become more sophisticated. Artificial intelligence (AI) is a rising technology with potential to assist medical physicists in their work. Exploration of AI integration into imaging medical physicist workloads is limited. In this review paper, we provide an overview of AI techniques, outline their potential usage in imaging medical physics, and discuss the limitations and challenges to clinical adoption of AI technologies.
Indexed as
Identifiers
40126762What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.