刺激性肠综合征的人工智能模型的诊断准确性和质量:系统性审查
Akshaya Srikanth Bhagavathula1, Ahmed Mourtada Al Qady2, Wafa A Aldhaleei3
1Department of Public Health, College of Health and Human Sciences, North Dakota State University, Fargo, ND 58102, United States. akshaya.bhagavathula@ndsu.edu.
人工智能 (AI) 模型显示出使用生物标志物诊断易怒肠综合征 (IBS) 的前景. 便微生物组分析获得了最高的准确性,但临床使用需要标准化.
科学领域:
- 胃肠道学和计算生物学
- 生物标志物发现和诊断
- 人工智能在医学中的应用
背景情况:
- 刺激性肠综合征 (IBS) 影响全球9%-12%的人口,由于主观症状和缺乏生物标志物,造成诊断挑战.
- 目前IBS的诊断方法受到症状变异性和缺乏客观生物标志物的限制.
结论:
- 人工智能通过整合复杂的生物标记数据来提高IBS诊断准确性的巨大潜力.
- 人工智能驱动的算法可以为IBS患者提供个性化治疗策略.
- 标准化协议和外部验证对于AI在IBS诊断中的临床适用性至关重要,因为目前的不一致性和有限的人口多样性.
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