ReviewCancers2024
Artificial Intelligence in Detection, Management, and Prognosis of Bone Metastasis: A Systematic Review.
Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance comparison and future perspectives of deep learning and classical machine learning in bone tumor applications: a systematic review (2019-2025).BMC medical informatics and decision making · 2026Pooled it
- Explainable Deep Learning Model for Predicting Overall Survival in Patients Receiving Palliative Radiotherapy for Bone Metastases.Current oncology (Toronto, Ont.) · 2026Article
- Predictive performance of image processing techniques in the diagnosis of bone metastasis: A meta-analysis of a confusion matrix.Oncology letters · 2026Article
- Bibliometric analysis of bone metastasis from prostate cancer research from 2007 to 2024.Discover oncology · 2026Article
- Artificial Intelligence and Machine Learning in Bone Metastasis Management: A Narrative Review.Current oncology (Toronto, Ont.) · 2026Review
- Autophagy in Rheumatoid Arthritis: Molecular Mechanisms, Diagnostic Biomarkers, and Emerging Therapeutic Strategies.Inflammation · 2026Review
- Multimodal AI fusion: integrating MRI with PET/CT, histopathology, and liquid biopsy for bone tumor diagnosis.Frontiers in oncology · 2026Review
- Review
- Applications and Performance of Artificial Intelligence in Spinal Metastasis Imaging: A Systematic Review.Journal of clinical medicine · 2025Review
- Integrating Artificial Intelligence in Orthopedic Care: Advancements in Bone Care and Future Directions.Bioengineering (Basel, Switzerland) · 2025Review
- Cancer metastasis to the bone: Mechanisms and animal models (Review).Oncology letters · 2025Review
- Review
- Regulation of metastatic organotropism.Trends in cancer · 2025Review
- Bone metastases from endocrine cancer: advances in diagnosis, treatment, and prevention.Frontiers in endocrinology · 2025Review
- Advancing bone tumor detection in older adults: the impact of AI-enhanced medical imaging.Frontiers in medicine · 2025Review
- AI-Assisted Detection and Localization of Spinal Metastatic Lesions.Diagnostics (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetastasis commonly occur in the bone tissue. Artificial intelligence (AI) has become increasingly prevalent in the medical sector as support in decision-making, diagnosis, and treatment processes. The objective of this systematic review was to assess the reliability of AI systems in clinical, radiological, and pathological aspects of bone metastases.
methodsWe included studies that evaluated the use of AI applications in patients affected by bone metastases. Two reviewers performed a digital search on 31 December 2023 on PubMed, Scopus, and Cochrane library and extracted authors, AI method, interest area, main modalities used, and main objectives from the included studies.
resultsWe included 59 studies that analyzed the contribution of computational intelligence in diagnosing or forecasting outcomes in patients with bone metastasis. Six studies were specific for spine metastasis. The study involved nuclear medicine (44.1%), clinical research (28.8%), radiology (20.4%), or molecular biology (6.8%). When a primary tumor was reported, prostate cancer was the most common, followed by lung, breast, and kidney.
conclusionsAppropriately trained AI models may be very useful in merging information to achieve an overall improved diagnostic accuracy and treatment for metastasis in the bone. Nevertheless, there are still concerns with the use of AI systems in medical settings. Ethical considerations and legal issues must be addressed to facilitate the safe and regulated adoption of AI technologies. The limitations of the study comprise a stronger emphasis on early detection rather than tumor management and prognosis as well as a high heterogeneity for type of tumor, AI technology and radiological techniques, pathology, or laboratory samples involved.
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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.