门诊流感样病例第四季度男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，对门诊流感样病例第四季度男性人数进行预测，为第四季度男性人数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。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。
对流感样病例数据进行预处理。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)，α1-α5为模型权重。
生成性别特征 GW(t)，但仅考虑男性病例数，计算公式为 GW(t) = γ1×male_cases(t)，γ1 为模型权重。
模型构建：构建预测模型，用以预测某天的男性流感样病例人数 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。
构建一个预测男性的流感样病例人数的模型:
sum_young_se1 = ∑F (t)，时间t在第四季度内。

For Influenza-Like Illness (ILI) surveillance, based on outpatient visit records from various medical institutions in Tongxiang, the annual number of outpatient and emergency visits, confirmed ILI cases, age group distribution and gender distribution are collected to predict the number of male outpatient ILI cases during the fourth quarter, providing novel ideas and methods for influenza prevention and control targeting male cases and sentinel hospital surveillance in the fourth quarter.
The gender data of ILI cases facilitates the rational allocation of medical resources, enabling adjustments to configurations such as medical staff, beds and medications to ensure the timeliness and effectiveness of medical services.
Data collection: Anonymized aggregated statistical data is obtained from various medical institutions in Tongxiang City, including daily outpatient and emergency visit volumes, number of individuals with ILI symptoms, age group distribution and gender distribution.
Preprocessing is conducted for the ILI dataset. Feature engineering: The age group feature AGW(t) is generated, 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.
The gender feature GW(t) is generated, considering only the number of male cases, with the formula: GW(t) = γ1×male_cases(t), where γ1 is the model weight.
Model construction: A prediction model is built to forecast the number of male 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 individuals with ILI symptoms on the current day;
C(t−n) represents the number of individuals with ILI symptoms on day t−n;
wn is the weight of C(t−n);
β1 and β2 are the weights of the derived features.
A model for predicting the number of male ILI cases is constructed as follows: sum_young_se1 = ∑F (t), where time t falls within the fourth quarter.

原始信息汇总

数据集概述

数据集名称

浙江省数据知识产权登记平台

数据集描述

浙江省数据知识产权登记平台是由浙江知识产权研究与服务中心推出的区块链数据知识产权登记系统。该平台支持数据知识产权登记、知识产权证书申请、原创作品登记确权、维权服务申请、维权证据出具、知识产权转让等多种场景，旨在从登记、确权、维权、交易等多个维度为创作者的知识产权提供保护。

关键词

区块链、知识产权、数据存证、知识产权存证、知识产权研究与服务中心、数据知识产权登记、浙江省数据知识产权登记平台

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第四季度男性人数，包含详细的年龄组和性别分布数据，每日更新，适用于流感防控和医疗资源调配。