自然语言处理从乳腺癌的书面知识库中提取有意义的信息:将书籍转化为数据
Giuseppe Catanuto1,2, Nicola Rocco1,3, Konstantina Balafa2
1G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Milan, Naples, Catania, Italy.
Breast care (Basel, Switzerland)
|November 6, 2023
概括
人工智能 (AI) 可以处理医疗文本以提取定量信息. 这项研究在专家撰写的书籍上训练了一个神经网络,以展示AI.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 医学教育在很大程度上依赖于来自书籍和论文的理论知识.
- 人工智能 (AI) 提供了从大型文本体中自动提取信息的潜力.
- 人工智能工具可以帮助分析教育材料和临床数据.
研究的目的:
- 探索人工智能的应用在处理医学文献的教育目的.
- 为了训练一个人工神经网络 (ANN) 使用 Word2Vec 在医学书籍的体.
- 评估从专业医学文本中获得定量信息的可行性.
主要方法:
- 通过公开招标,选择了30名医学专家.
- 收购了六本关于乳腺癌知识的书籍,作者或共同作者是专家.
- 在获得的书籍库上使用Word2Vec技术培训了一个ANN.
主要成果:
- 该语料库包括大约22亿个单词,处理成300维向量.
- 为了评估矢量关系,在不同单词之间评估了等号相似性.
- 证明了从医学文本中提取定量信息的潜力.
结论:
- 这项研究代表了利用人工智能从文本体中提取正式信息的初步步骤.
- 由人工智能驱动的增强阅读可以产生新的假设,并估计专家知识中的关联.
- 词嵌入技术显示出分析临床笔记和预测结果的前景,有助于生成"现实世界的证据".
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