人工智能实现了音频到文本的转录和翻译,以简化药监数据收集和药物不良反应报告
Tasneem Hussain1, Pooja Solanki Mishra1, Ashutosh Tiwari1
1Department of Pharmacology, Mahatma Gandhi Memorial Medical College, Indore, Madhya Pradesh, India.
Perspectives in clinical research
|November 10, 2025
概括
人工智能系统通过准确地转录,翻译和评估因果关系,显著改善药物不良反应 (ADR) 报告,简化药物监督并提高患者安全.
科学领域:
- 药监和药物安全 药监和药物安全
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 药物不良反应 (ADR) 报告对于患者的安全至关重要,但由于人工效率低下和资源限制,它面临着挑战.
- 人工智能 (AI) 为简化ADR报告流程提供了一个潜在的解决方案.
研究的目的:
- 评估人工智能支持系统的音频到文本转录,翻译,ADR表格填写和因果关系评估的性能.
- 在现实世界药物监督环境中评估AI系统的功能.
主要方法:
- 一项涉及100名参与者 (50名医疗保健专业人员,50名患者) 的比较,横截面研究,他们提供了录音ADR报告.
- 人工智能系统处理记录用于转录,翻译和ADR表格生成,通过WER,CER,SER,BLEU和TER等指标测量性能.
- 人工智能因果关系评估与专家评估进行了比较.
主要成果:
- 人工智能系统在转录 (WER <0.05,CER <0.04,SER <0.35) 和翻译 (BLEU >0.85,TER <0.05) 中实现了高精度.
- 填写ADR表格显示近乎完美的准确性,医疗保健专业人员和患者之间的因果关系评估一致 (P=1).
结论:
- 支持人工智能的系统可以有效地简化ADR报告,提高准确性和一致性.
- 将人工智能整合到药物监管中可以减少工作量,增加报告率,并改善全球健康结果.
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