ReviewFrontiers in medicine2025
Advancing bone tumor detection in older adults: the impact of AI-enhanced medical imaging.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- AI in Musculoskeletal Imaging: An End-to-End Perspective.Journal of clinical medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma presents unique challenges in diagnosis and management, particularly among older adults, who often experience distinct clinical presentations and treatment complications. As the global demographic of individuals aged 65 and older continues to expand, the need for effective strategies to address osteosarcoma in this group becomes increasingly urgent. Medical imaging plays a major role in the detection and monitoring of bone tumors, yet traditional imaging approaches face significant challenges when applied to older adults, including age-related physiological changes and comorbidities. Recent advancements in Artificial Intelligence provide transformative potential to enhance medical imaging for osteosarcoma detection in older adults. AI-driven technologies can improve image acquisition, reduce artifacts, and automate tumor detection and segmentation, thereby increasing diagnostic accuracy and optimizing treatment strategies. This mini-review explores the critical role of AI-enhanced medical imaging in overcoming the unique challenges of diagnosing osteosarcoma in older adults, emphasizing the need for tailored algorithms and protocols that consider the specific anatomical and physiological characteristics of this vulnerable population.
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What Socratic 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 Socratic graph.