门诊流感样病例女性人数预测模型数据

针对流感样病例监测，基于桐乡各医疗机构门诊就诊记录，获取全年门急诊就诊人数、流感样病例确诊人数、年龄组及性别分布，对门诊流感样病例女性人数进行预测，为女性流感防控工作及哨点医院监测工作提供新的思路和方法。流感样病例的性别数据有助于医疗资源的合理调配，可以调整医护人员、床位、药物等资源的配置，确保医疗服务的及时性和有效性。1.数据采集：从桐乡市各医疗机构获取匿名化样本统计数据，包括每日门急诊就诊人数、流感样病例症状人数、年龄组及性别分布。
2．数据预处理：对流感样病例数据进行预处理，消除异常值和噪声，平滑数据，减少随机波动。
3. 特征工程：
生成年龄组特征 AGW(t)，计算公式为 AGW(t)=α1×age_0_5(t) +α2×age_5_15(t)+α3×age_15_25(t)+α4×age_25_60(t) + α5×age_60_plus(t)，其中α1-α5 为模型权重。
生成性别特征 GW(t)，但仅考虑女性病例数，计算公式为 GW(t) = γ1×female_cases(t)，γ1 为模型权重。
4. 模型构建：构建预测模型，用以预测某天的女性流感样病例人数 F(t)。预测公式为 F(t)=w1×C(t−1)+ w2×C(t−2) + ... + wn×C(t−n)+β1AGW(t)+β2GW(t)，其中：
C(t)代表当天的流感样病例症状人数；
C(t−n) 为 t−n日的流感样病例症状人数；
wn为 C(t−n)的权重；
β1和β2是衍生特征的权重。

This dataset is developed for influenza-like illness (ILI) surveillance, utilizing outpatient visit records from medical institutions across Tongxiang. It collects annual statistics covering the total number of outpatient and emergency visits, confirmed ILI cases, age group distribution and gender distribution, aiming to predict the number of female outpatient ILI cases, thereby providing novel insights and approaches for female influenza prevention and control as well as sentinel hospital surveillance work. Gender data of ILI cases facilitates the rational allocation of medical resources, including adjusting the configuration of medical staff, beds, medications and other resources, to ensure the timeliness and effectiveness of medical services.
1. Data Collection: Obtain anonymized sample statistical data from various medical institutions in Tongxiang, including daily number of outpatient and emergency visits, number of ILI symptomatic cases, age group distribution and gender distribution.
2. Data Preprocessing: Preprocess the ILI-related data by eliminating outliers and noise, smoothing the data to reduce random fluctuations.
3. Feature Engineering:
- Generate the age group feature AGW(t), with the calculation formula: AGW(t)=α1×age_0_5(t) +α2×age_5_15(t)+α3×age_15_25(t)+α4×age_25_60(t) + α5×age_60_plus(t), where α1-α5 are model weights.
- Generate the gender feature GW(t), which only considers the number of female cases, with the calculation formula: GW(t) = γ1×female_cases(t), where γ1 is the model weight.
4. Model Construction: Construct a predictive model to forecast the number of female ILI cases F(t) on a given day. The prediction formula is:
F(t)=w1×C(t−1)+ w2×C(t−2) + ... + wn×C(t−n)+β1AGW(t)+β2GW(t)
Where:
- C(t) represents the number of ILI symptomatic cases on day t;
- C(t−n) represents the number of ILI symptomatic cases on day t−n;
- wn is the weight of C(t−n);
- β1 and β2 are the weights of the derived features.

搜集汇总

数据集介绍

特点

该数据集用于预测门诊流感样病例中的女性人数，包含每日门急诊就诊人数、流感样病例症状人数、年龄组及性别分布等信息，数据每日更新，适用于流感监测和医疗资源调配。