新型隐球菌脑膜炎智能诊疗系统技术方案

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一、核心算法实现

1. 术前真菌载量预测模型

伪代码实现：

class FungalLoadPredictor:def __init__(self):self.temporal_cnn = TemporalConvNet()  # 时间卷积网络self.attention = TransformerEncoder() # 注意力机制def predict(self, csg_data):# 输入维度：[batch_size, time_steps, features]temporal_features = self.temporal_cnn(csf_data)weighted_features = self.attention(temporal_features)return MLP(weighted_features)  # 多层感知机输出预测值

流程图：

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2. 术中手术路径规划算法

伪代码实现：

def reinforcement_learning_planning(patient_anatomy):env = SurgicalEnv(patient_anatomy)  # 手术环境模拟agent = PPOAgent()  # 近端策略优化算法for epoch in training_epochs:state = env.reset()while not done:action = agent.get_action(state)next_state, reward = env.step(action)agent.update_buffer(state, action, reward)state = next_stateagent.train()return agent.get_optimal_path()

流程图：

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二、系统集成方案

1. 系统交互流程图