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

IF 3 4区 医学 Q2 ONCOLOGY Future oncology Pub Date : 2024-01-01 Epub Date: 2024-08-12 DOI:10.1080/14796694.2024.2385296
Alain Chebly
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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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人工智能时代的癌症细胞遗传学:塑造染色体分析的未来。
人工智能(AI)在过去几年中发展迅速,尤其是在改善诊断的医学领域。在临床细胞遗传学中,人工智能正成为分析染色体异常和提高精确度的关键。然而,现有软件缺乏经验用户的学习能力。人工智能的整合已扩展到基因组数据分析、个性化医疗和研究领域,但伦理问题也随之而来。在本文中,我们将讨论细胞遗传学检验解读全自动化所面临的挑战,并重点介绍其重要性和益处。
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来源期刊
Future oncology
Future oncology ONCOLOGY-
CiteScore
5.40
自引率
3.00%
发文量
335
审稿时长
4-8 weeks
期刊介绍: Future Oncology (ISSN 1479-6694) provides a forum for a new era of cancer care. The journal focuses on the most important advances and highlights their relevance in the clinical setting. Furthermore, Future Oncology delivers essential information in concise, at-a-glance article formats - vital in delivering information to an increasingly time-constrained community. The journal takes a forward-looking stance toward the scientific and clinical issues, together with the economic and policy issues that confront us in this new era of cancer care. The journal includes literature awareness such as the latest developments in radiotherapy and immunotherapy, concise commentary and analysis, and full review articles all of which provide key findings, translational to the clinical setting.
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