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Cancer cytogenetics in the era of artificial intelligence: shaping the future of chromosome analysis.

Alain Chebly
Published in: Future oncology (London, England) (2024)
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.
Keyphrases
  • artificial intelligence
  • data analysis
  • copy number
  • machine learning
  • big data
  • deep learning
  • papillary thyroid
  • squamous cell carcinoma
  • decision making
  • lymph node metastasis
  • genome wide