ArticleFuture oncology (London, England)2024
Cancer cytogenetics in the era of artificial intelligence: shaping the future of chromosome analysis.
Article in Future oncology (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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Who cites it
11 citing papers in PubMed.
- Article
- Cytogenetics in the genomics era: why karyotyping still matters.BMC medical genomics · 2026Review
- AI in hematology: A new frontier for nursing practice and patient care.Journal of family medicine and primary care · 2026Review
- Artificial Intelligence in Haematologic Diagnostics: Current Applications and Future Perspectives.Acta haematologica · 2026Review
- Recent advances in the detection technologies for balanced chromosomal rearrangements.Frontiers in genetics · 2026Review
- Assessing the reliability of ChatGPT in cytogenetic reporting and interpretation: implications for clinical use.Molecular cytogenetics · 2025Article
- Incorporating automation in a cytogenetics laboratory: three practitioners' perspectives on benefits and limitations.Molecular cytogenetics · 2025Review
- Review
- Holistic precision wellness: Paving the way for next-generation precision medicine (ngPM) with AI, biomedical informatics, and clinical medicine.FASEB bioAdvances · 2025Article
- Optical genome mapping with whole genome sequencing identifies complex chromosomal structural variations in acute leukemia.Frontiers in genetics · 2025Article
- Complex karyotypes in hematologic disorders: a 12-year single-center study from Lebanon.Frontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has rapidly advanced in the past years, particularly in medicine for improved diagnostics. In clinical cytogenetics, AI is becoming crucial for analyzing chromosomal abnormalities and improving precision. However, existing software lack learning capabilities from experienced users. AI integration extends to genomic data analysis, personalized medicine and research, but ethical concerns arise. In this article, we discuss the challenges of the full automation in cytogenetic test interpretation and focus on its importance and benefits.
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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.