ArticleJMA journal2025
Use of AI in Diagnostic Imaging and Future Prospects.
Article in JMA journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed.
- From pixels to precision: a narrative review of AI-driven 3D morphological analysis and digital twinning in alveolar cleft management.Translational pediatrics · 2026Review
- Anemia in young women: determinants and artificial intelligence-based management approaches.Frontiers in artificial intelligence · 2026Review
- Faculty perspectives on artificial intelligence's adoption in the health sciences education: a multicentre survey.Frontiers in medicine · 2025Article
- Artificial intelligence-assisted organoid construction in congenital heart disease: current applications and future prospects.Frontiers in bioengineering and biotechnology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The integration of artificial intelligence (AI) into medical practices has transformed fields like gastroenterological surgery. AI predicts patient prognoses using clinical and pathological data and develops technologies that create three-dimensional (3D) models for surgical simulations, thereby enhancing surgical precision and care quality. Methods: At our facility, AI-driven diagnostic and treatment systems have been developed under the "Strategic Innovation Creation Program" by the Cabinet Office. Our research focuses on perioperative care by constructing 3D models from preoperative imaging data to develop surgical support systems for preoperative simulations and navigation during surgery. Additionally, we use deep learning to predict disease progression and complications and natural language processing to analyze electronic medical records to predict postoperative complications. Results: AI-based surgical support systems effectively convert two-dimensional imaging data into 3D models, thereby improving surgical precision. Predictive models for disease progression and complications developed using deep learning have high accuracy. AI applications in diagnostic imaging enable early detection and improved treatment planning. AI-based tools for informed consent and patient support enhance patient understanding and satisfaction. Conclusions: AI revolutionizes medical practices by improving diagnostic accuracy, surgical precision, and patient outcomes. Future projects will integrate remote diagnostic and treatment planning; leverage AI for comprehensive, high-quality care; and support work-style reforms for healthcare professionals. Advancements in AI will overcome current medical challenges and enhance the communication between physicians and patients.
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What 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.