人工智能的当前应用在 Sarcoidosis 中
Dana Lew1, Eyal Klang2, Shelly Soffer3
1Division of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lung
|September 21, 2023
概括
人工智能 (AI),包括机器学习和深度学习,在诊断沙丘病和预测结果方面表现有前途. 需要进一步的研究来克服数据限制,以便在这种罕见疾病中更广泛地应用人工智能.
科学领域:
- 医疗信息学医学信息学
- 计算病理学计算病理学
- 医学中的人工智能
背景情况:
- Sarcoidosis是一种多系统的炎症性疾病,具有多种不同的临床表现.
- 由于疾病的复杂性,准确的诊断和预后仍然具有挑战性.
- 人工智能 (AI) 提供了新的方法来研究瘤发病.
研究的目的:
- 审查人工智能的当前应用,包括机器学习,深度学习和放射学,用于研究型发病.
- 识别人工智能的潜力,以改善 Sarcoidosis 的诊断和预后.
- 探索人工智能的未来方向在 Sarcoidosis 研究.
主要方法:
- 系统地在在线数据库中搜索有关肉类瘤和人工智能的文章.
- 关键词包括: Sarcoidosis, 机器学习, 人工智能, 放射学和 深度学习.
- 排除非英语文章,并审查标题/摘要的相关性.
主要成果:
- 机器学习有助于诊断肺部型硬化症和心脏预后.
- 深度学习被广泛用于肺性沙尔科毒性病的诊断.
- 放射学主要区分了类瘤与恶性瘤.
结论:
- 目前,人工智能在肉病中的应用受疾病的稀有性和小型数据集的限制.
- 对于其他系统性疾病,现有的人工智能方法可能可以适应沙尔科毒症.
- 未来的人工智能应用可能包括表型发现,生物标志物识别和治疗优化.
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