<p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-13b06998c4da2c95.jpg?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><h1><strong>内容简介</strong></h1><p>本文内容为该项目V1.0版本的内容。</p><p>中医问诊系统第一版系统前后台展示内容。</p><h1><strong>展示页面</strong></h1><p><strong>1.信息确认</strong> </p><p>用户注册和登录系统的时候都需要进行有效信息的确认，因为有些参数是构建好的问诊模型中比较重要的参数信息。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-fdff1ed808c4ea2d.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>2.问诊答题</strong> </p><p>基于18个项目的内容和对应的300道问诊提供进行答题，总体时间约20分钟，题目来源取自朱文封老师的书籍，每道问题分4个选项。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-903449b099035c46.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>3.回归辩证</strong> </p><p>回归数据的柱状图由于本地安全策略加载内容无法显示单独拿出来。这里回归辩证使用的是基于Sklearn进行建模的直接计算的结果，使用的是混合回归模型，在之前的介绍的论文中有提到。回归辩证主要包括 <strong>八纲辨证、病因辩证、津液辩证、气血辩证、脏腑辩证、其他辩证</strong> 六个组成部分的数据可视化图表显示。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-5d10685ee7ff6496.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-91ac549312a7e51d.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>4.证型分类</strong> </p><p>根据模型计算的结果在700+的证素辩证组成的名称中通过RNN神经网络计算的模型得到概率最高10个结果辩证名称进行显示。并提供辅助治疗的 <strong>中医治疗方式、方剂配伍、使用方法</strong> 等等。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-f6843ea6a7ed721c.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>5.体质分类</strong> </p><p>根据模型计算的结果在人体的9种体制中进行RNN神经网络的分类业务，一共分 <strong>平和质、气虚质、阳虚质、阴虚质、痰湿质、湿热质、血瘀质、气郁质、特禀质</strong> 9种体制。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-73a3bef3f06a4c5a.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>6.水果推荐</strong> </p><p>根据模型计算的结果在养生方案中进行RNN神经网络的水果推荐业务。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-56a2dcaa03366843.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>7.五谷推荐</strong> </p><p>根据模型计算的结果在养生方案中进行RNN神经网络的谷物推荐业务。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-514153a7c8b060ea.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>8.茶饮推荐</strong> </p><p>根据模型计算的结果在养生方案中进行RNN神经网络的茶饮推荐业务。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-0ec4b413536a4646.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p><strong>9.蔬菜推荐</strong> </p><p>根据模型计算的结果在养生方案中进行RNN神经网络的蔬菜推荐业务。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-39c94a8f80c5dcef.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><h1><strong>后台管理</strong></h1><p>用于记录用户每一次的答题结果数据。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-53ed6e14e89d4d5a.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p>算法模型构建的问题参数内容。</p><p class="image-package"><img class="uploaded-img" src="https://upload-images.jianshu.io/upload_images/24367109-884beb7356643e77.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240" width="auto" height="auto"/></p><p>
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