CN111656357A - 基于人工智能的眼科疾病诊断建模方法、装置及*** - Google Patents
基于人工智能的眼科疾病诊断建模方法、装置及*** Download PDFInfo
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Abstract
一种基于人工智能的眼科疾病诊断建模方法、装置及***,该方法包括建立眼科图像数据集和眼科非图像疾病诊断问卷数据集(S101);采用眼科图像数据集训练第一神经网络模型,得到第一分类模型(S102);采用眼科非图像疾病诊断问卷数据集训练第二分类模型(S103);融合第一分类模型和第二分类模型,得到目标分类网络模型,并将基于目标分类网络模型输出的测试结果作为对眼科疾病进行诊断得到的诊断结果(S104)。通过该方法能够集成临床、眼科影像,以及病患个人信息辅助进行眼科诊断,能够使得人工智能技术更好地辅助眼科疾病诊断建模,有效提升眼科全种类疾病诊断建模的智能化和精准度,提升诊断效果。
Description
PCT国内申请,说明书已公开。
Claims (26)
- PCT国内申请,权利要求书已公开。
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PCT/CN2018/083393 WO2019200535A1 (zh) | 2018-04-17 | 2018-04-17 | 基于人工智能的眼科疾病诊断建模方法、装置及*** |
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CN112233087A (zh) * | 2020-10-14 | 2021-01-15 | 武汉楚精灵医疗科技有限公司 | 一种基于人工智能的眼科超声疾病诊断方法和*** |
CN112418303A (zh) * | 2020-11-20 | 2021-02-26 | 浙江大华技术股份有限公司 | 一种识别状态模型的训练方法、装置及计算机设备 |
CN112446860A (zh) * | 2020-11-23 | 2021-03-05 | 中山大学中山眼科中心 | 一种基于迁移学习的糖尿病黄斑水肿自动筛查方法 |
CN112884729A (zh) * | 2021-02-04 | 2021-06-01 | 北京邮电大学 | 基于双模态深度学习的眼底疾病辅助诊断方法和装置 |
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CN115147668A (zh) * | 2022-09-06 | 2022-10-04 | 北京鹰瞳科技发展股份有限公司 | 疾病分类模型的训练方法、疾病分类的方法及相关产品 |
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US11636340B2 (en) | 2023-04-25 |
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