以人工智能驱动的调度为中心的解决方案，旨在优化员工分配、增强患者护理和简化医院运营。它集成了高级调度算法，这些算法优先考虑员工偏好，确保指定的休息日，并根据需求和可用性动态分配医生、护士和接待员。
A solution centered around AI-driven scheduling, designed to optimize staff allocation, enhance patient care, and streamline hospital operations. It integrates advanced scheduling algorithms that prioritize staff preferences, ensure designated days off, and dynamically allocate doctors, nurses, and receptionists based on demand and availability. (2024-01-27, Python, 0KB, 下载0次)
基于Qt C++实现的新冠肺炎疫情实时数据可视化显示。主要包括新型冠状病毒肺炎疫情数据实时查看,确诊 疑似 治愈 死亡数据趋势折线图,各省市和海外数据树形显示,最新动态和辟谣信息显示等,数据源来自腾讯新闻接口,数据格式为JSON。用于...
Real time data visualization of COVID-19 epidemic based on Qt C++. It mainly includes real-time viewing of COVID-19 epidemic data, trend line chart of confirmed and suspected cured deaths, tree display of provincial and overseas data, display of the latest news and rumor dispelling information, etc. The data source is Tencent News interface, and the data format is JSON. For (2020-03-29, C++, 13973KB, 下载0次)
本项目通过爬取腾讯、新浪、丁香园等疫情数据,获取新冠肺炎相关数据,并整合为api数据,做法简单粗暴,类似于端口转发。数据包含口罩预约、同乘车辆、疫情小区、数据分析、国内外详细数据、实时新闻动态、确诊人员信息流动轨迹、疫情谣言等。
This project obtains COVID-19 related data by crawling the epidemic data of Tencent, Sina, DXY, etc., and integrates them into api data, which is simple and rough, similar to port forwarding. The data includes mask reservation, passenger car, epidemic area, data analysis, detailed data at home and abroad, real-time news trends, information flow track of confirmed personnel, epidemic rumors, etc. (2022-09-01, Java, 45614KB, 下载0次)
COVID-19-tracker,北航大数据高精尖中心研究团队进行数据来源的整理与获取,利用自然语言处理等技术从已公开全国4626确诊患者轨迹中抽取了基本信息(性别、年龄、常住地、工作、武汉 湖北接触史等)、轨迹(时间、地点、交通工具、事件)及病患关系形成结构化信息
COVID-19-tracker, the research team of Beihang Big Data High Precision Center collated and obtained data sources, and used natural language processing and other technologies to extract basic information (gender, age, permanent residence, work, Wuhan Hubei contact history, etc.), track (time, place, transportation, events), and patient relationship from the 4626 confirmed patient tracks published nationwide to form structured information (2023-05-14, Others, 3240KB, 下载0次)