ArticleWorld journal of clinical cases2025
Artificial intelligence and the impact of multiomics on the reporting of case reports.
Article in World journal of clinical cases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Immune crosstalk in Alzheimer's and Parkinson's disease: insights from Drosophila models into the brain-peripheral immune axis.Frontiers in immunology · 2026Review
- Liquid Biopsy and Multi-Omic Biomarkers in Breast Cancer: Innovations in Early Detection, Therapy Guidance, and Disease Monitoring.Biomedicines · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence (AI) and multiomics has transformed clinical and life sciences, enabling precision medicine and redefining disease understanding. Scientific publications grew significantly from 2.1 million in 2012 to 3.3 million in 2022, with AI research tripling during this period. Multiomics fields, including genomics and proteomics, also advanced, exemplified by the Human Proteome Project achieving a 90% complete blueprint by 2021. This growth highlights opportunities and challenges in integrating AI and multiomics into clinical reporting. A review of studies and case reports was conducted to evaluate AI and multiomics integration. Key areas analyzed included diagnostic accuracy, predictive modeling, and personalized treatment approaches driven by AI tools. Case examples were studied to assess impacts on clinical decision-making. AI and multiomics enhanced data integration, predictive insights, and treatment personalization. Fields like radiomics, genomics, and proteomics improved diagnostics and guided therapy. For instance, the "AI radiomics, genomics, oncopathomics, and surgomics project" combined radiomics and genomics for surgical decision-making, enabling preoperative, intraoperative, and postoperative interventions. AI applications in case reports predicted conditions like postoperative delirium and monitored cancer progression using genomic and imaging data. AI and multiomics enable standardized data analysis, dynamic updates, and predictive modeling in case reports. Traditional reports often lack objectivity, but AI enhances reproducibility and decision-making by processing large datasets. Challenges include data standardization, biases, and ethical concerns. Overcoming these barriers is vital for optimizing AI applications and advancing personalized medicine. AI and multiomics integration is revolutionizing clinical research and practice. Standardizing data reporting and addressing challenges in ethics and data quality will unlock their full potential. Emphasizing collaboration and transparency is essential for leveraging these tools to improve patient care and scientific communication.
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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.