Evolving Artificial Intelligence (AI) at the Crossroads: Potentiating Productive vs. Declining Disruptive Cancer Research.

IF 4.5 2区 医学 Q1 ONCOLOGY Cancers Pub Date : 2024-10-29 DOI:10.3390/cancers16213646
Nilesh Kumar Sharma, Sachin C Sarode
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Abstract

Artificial intelligence (AI), encompassing several tools and platforms such as artificial "general" intelligence (AGI) and generative artificial intelligence (GenAI), has facilitated cancer research, enhancing productivity in terms of research publications and translational value for cancer patients. AGI tools, such as ChatGPT, assist preclinical and clinical scientists in identifying tumor heterogeneity, predicting therapy outcomes, and streamlining research publications. However, this perspective review also explores the potential of AI's influence on cancer research with regard to its impact on disruptive sciences and discoveries by preclinical and clinical scientists. The increasing reliance on AI tools may compromise biological intelligence, disrupting abstraction, creativity, and critical thinking. This could contribute to the declining trend of disruptive sciences, hindering landmark discoveries and innovations. This perspective review narrates the role of different forms of AI in the potentiation of productive cancer research and the potential disruption of disruptive sciences due to AI's influence.

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处于十字路口的不断发展的人工智能(AI):癌症研究的生产性潜能与破坏性衰退。
人工智能(AI)包括多种工具和平台,如人工 "通用 "智能(AGI)和生成式人工智能(GenAI),它促进了癌症研究,提高了研究出版物的生产率和对癌症患者的转化价值。ChatGPT 等 AGI 工具可帮助临床前和临床科学家识别肿瘤异质性、预测治疗结果并简化研究论文的发表。不过,本视角综述还探讨了人工智能对癌症研究的潜在影响,即其对颠覆性科学以及临床前和临床科学家的发现的影响。对人工智能工具的日益依赖可能会损害生物智能,破坏抽象性、创造性和批判性思维。这可能会导致颠覆性科学的衰退趋势,阻碍具有里程碑意义的发现和创新。本视角综述阐述了不同形式的人工智能在促进富有成效的癌症研究中的作用,以及人工智能的影响可能对颠覆性科学造成的破坏。
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来源期刊
Cancers
Cancers Medicine-Oncology
CiteScore
8.00
自引率
9.60%
发文量
5371
审稿时长
18.07 days
期刊介绍: Cancers (ISSN 2072-6694) is an international, peer-reviewed open access journal on oncology. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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