探索人工智能语言模型在产科的潜力,以胎儿医学为重点:对Perplexity人工智能模型的评估。

IF 1.6 3区 医学 Q3 OBSTETRICS & GYNECOLOGY Fetal Diagnosis and Therapy Pub Date : 2024-01-01 Epub Date: 2023-11-30 DOI:10.1159/000535345
Angel Chimenea, Lutgardo García-Díaz, Guillermo Antiñolo
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引用次数: 0

摘要

由自然语言处理和预训练语言模型驱动的人工智能(AI)语言模型已经证明了在自然语言处理任务(包括文本生成和理解)方面的熟练程度。这些模型可以通过提供全面和准确的信息、帮助决策过程以及促进医生和患者之间的有效沟通来帮助胎儿医学的医疗保健专业人员。然而,人工智能语言模型在胎儿医学中的整合面临着局限性和挑战。道德考虑、隐私问题和潜在的算法偏见是需要解决的重要因素。人工智能模型的透明度和可解释性对于确保其可信度至关重要,需要进行严格的验证研究来评估其性能。医疗保健专业人员参与这些模型的开发和实施对于保持以患者为中心的方法和减轻过度依赖人工智能系统的风险至关重要。本文探讨了在胎儿医学背景下使用人工智能语言模型的潜在好处和注意事项。
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Exploring the Potential of Artificial Intelligence Language Models in Obstetrics with a Focus on Fetal Medicine: An Evaluation of the Perplexity AI Model.
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来源期刊
Fetal Diagnosis and Therapy
Fetal Diagnosis and Therapy 医学-妇产科学
CiteScore
4.70
自引率
9.10%
发文量
48
审稿时长
6-12 weeks
期刊介绍: The first journal to focus on the fetus as a patient, ''Fetal Diagnosis and Therapy'' provides a wide range of biomedical specialists with a single source of reports encompassing the common discipline of fetal medicine.
期刊最新文献
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