瘤学中的人工智能:当前状态和可能性 (综述)
Abhavya Roy1, Apurva Bhoyar2, Ashok Ahirwar3
1University College of Medical Sciences, Guru Teg Bahadur Hospital, Delhi 110095, India.
Medicine international
|March 13, 2026
概括
人工智能 (AI) 正在通过先进的机器学习改变瘤学,以更好地诊断癌症和个性化治疗. 然而,数据偏差和监管障碍等挑战阻碍了其广泛的临床采用.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 人工智能 (AI) 越来越多地融入瘤学,影响诊断准确性,预后和个性化治疗策略.
- 机器学习 (ML) 和深度学习 (DL) 模型,包括卷积神经网络 (CNN) 和变压器,在癌症研究中显示出重大前景.
研究的目的:
- 对瘤学当前的人工智能应用进行批判性审查,涵盖成像,数字病理学,结果预测和治疗计划.
- 综合最近的进展,并确定阻碍人工智能在癌症治疗中的临床转化挑战.
主要方法:
- 对各种瘤学领域的人工智能应用的当代文献的综述.
- 分析机器学习和深度学习模型在诸如病变检测,瘤分级和生存预测等任务中的性能.
主要成果:
- 人工智能模型在特定的瘤学任务中表现出专家级或更高的准确性,包括图像分析和结果预测.
- 临床实施存在重大障碍,例如数据集偏差,有限的概括性,缺乏标准化,解释性问题和监管障碍.
结论:
- 人工智能具有巨大的潜力,可以推进精确瘤学和改善全球癌症结果.
- 通过多学科合作,前性验证和道德治理克服挑战,对于实现AI在癌症护理方面的全部潜力至关重要.
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