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Model recipes for incoming workload prediction

Model recipes for incoming workload prediction
用于预测传入工作负载的模型配方
批准号:
524631-2018
负责人:
TAGHIPOUR, SHARAREH
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
Intelerad是一家加拿大公司,总部设在蒙特利尔,在卡尔加里 ** 和多伦多设有办事处。该公司在加拿大办事处设计和开发医疗成像软件解决方案,使医院、成像中心和放射学阅读小组能够访问和解释医疗图像,以 ** 建立诊断。通过使用直接来源于Intelerad的图片存储和通信 ** 系统(PACS)的实时事件和指标,Intelerad的千里眼预测分析仪表板旨在 ** 为关键运营人员和放射科医生提供深入的见解,以了解成像企业或实践操作。该仪表板还可以精确定位整个成像链的优势和工作流程效率低下的情况,跟踪成像 ** 部门和放射科医生的特定生产率数据,并推断系统级数据和指标,例如研究 ** 量或预期的传入工作量和订单周转时间(达特)以及达特率。Intelerad目前希望增强其推断和预测上述系统级数据 ** 和指标的能力,即预期的输入工作量、订单周转时间(达特)和订单未命中达特率。在这个项目中,Ryerson和Intelerad调查了输入的工作量数据流和放射科医生的生产力 ** 模式,并根据研究结果,提出了改进或新方法,以完全开发概念预测模型的 ** 证明。
英文摘要
Intelerad is a Canadian company with its Head Office in Montreal and additional Canadian offices in Calgary**and Toronto. The company designs and develops medical imaging software solutions from its Canadian offices**which allow hospitals, imaging centers, and radiology reading groups to access and interpret medical images in**order to establish a diagnosis.**By using real-time events and metrics sourced directly from Intelerad's Picture Archiving and Communication**System (PACS), Intelerad's Clairvoyance Predictive Workload Analytics dashboard is being designed to**provide deep insights for key operational staff and radiologists into imaging enterprises or practice operations.**The dashboard also pinpoints strengths and workflow inefficiencies across the imaging chain, tracks imaging**department and radiologist-specific productivity data, and infers system-level data and indicators, such as study**volume or expected incoming workload and order turn-around time (TAT) and miss TAT rate.**Intelerad currently would like to enhance its ability to infer and predict the aforementioned system-level data**and indicators namely expected incoming workload, order Turn Around Time (TAT), and order Miss TAT rate.**In this project, Ryerson and Intelerad investigate incoming workload data stream and radiologist productivity**patterns and based on research findings, propose enhancements or new approaches altogether to the developed**proof of concept predictive models.
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  • 财政年份:
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