智能医疗应用中的生成人工智能和大语言模型:当前状态和未来前景
Md Asraful Haque1, Hifzur R Siddique2
1Interdisciplinary Center for Artificial Intelligence, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh 202002, India.
Computational biology and chemistry
|August 9, 2025
概括
生成型人工智能 (AI) 和大型语言模型 (LLM) 为智能医疗提供了变革性的潜力,有助于个性化护理和早期疾病检测. 解决人工智能偏见和道德问题等挑战对于未来的整合至关重要.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
背景情况:
- 由于气候变化,息地破坏和人口老龄化,全球疾病发病率不断上升,需要创新的医疗保健解决方案.
- 生成型人工智能和LLM代表了机器学习的重大进步,像GPT和BERT这样的模型在医疗应用中显示出希望.
研究的目的:
- 审查生成AI和LLM在智能医疗保健中的潜在好处.
- 识别和讨论与在医疗保健中实施这些技术相关的挑战和伦理考虑.
主要方法:
- 进行了系统的文献审查.
- 在包括PubMed,PMC,Cochrane Library,Google Scholar和Web of Science在内的主要数据库中进行了搜索.
- 关键词集中在生成人工智能,LLM和医疗保健应用程序上.
主要成果:
- 生成型人工智能和LLM可以处理和分析用于医疗保健应用的庞大数据集.
- 潜在的应用包括智能虚拟健康助理,个性化患者护理计划和早期疾病检测/干预.
- 目前正在进行的研究强调了这些人工智能模型在医学中的变革能力.
结论:
- 生成型人工智能和LLM在推进智能医疗保健方面具有重大前景.
- 诸如人工智能偏见,缺乏可解释性,道德困境和整合问题等关键挑战需要仔细考虑和解决.
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