CREATE Training Program in Medical Informatics: Preparing Canada's Workforce for Health Data of Tomorrow
创建医疗信息学培训计划:让加拿大劳动力为明天的健康数据做好准备
基本信息
- 批准号:555366-2021
- 负责人:
- 金额:$ 10.79万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Training Experience
- 财政年份:2021
- 资助国家:加拿大
- 起止时间:2021-01-01 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Digital health is transforming the way Canadians access health care, altering clinical workflows while providing unique opportunities for computing sciences to revolutionize health and operational decision making. While G7 governments were set to focus on this topic in 2020, specifically on the Centrality of Digital Health Collaboration to Progress, the unprecedented impact of the COVID-19 pandemic has made clear the critical need to understand the significance of data and its interpretation for decision making. As Canada and the world tackle questions ranging from high level policies on population and resources to day-to-day predictive analysis of patient outcomes, skilled workforce preparedness in informatics and computing sciences with necessary context in health data and its application is vital. The silver lining of the current pandemic may lie in resources that Canada is investing to prepare our collective response, critically aided by data. While AI and informatics show great promise in rapid analysis of next-generation large scale data, future workers will require highly specialized training due to the unique nature of health data. Information and Communications Technology Council of Canada projects demand for >300K skilled workers with expertise in computational sciences by 2023. Of those, >120K will contribute to health and biotechnology, one of six innovation areas of the future economy. To forge successful careers in the new job market, HQP in our CREATE program will not only learn state of the art in computing and informatics, but also develop a depth and breadth of understanding of the health data context and a flexibility in approach that allows them to stay current in such a rapidly changing setting. We partner with key stakeholders in medical informatics, and complement technical training with innovations in problem solving, experiential learning and professional growth. To solidify Canada's competitive advantage in the global space, we contribute to concerted efforts to train computer scientists with multidisciplinary experience and by engaging diverse groups including women, Black and Indigenous communities, internationally-educated professionals, those transitioning careers, and persons with disabilities.
数字医疗正在改变加拿大人获得医疗保健的方式,改变临床工作流程,同时为计算科学提供独特的机会来彻底改变健康和运营决策。虽然七国集团政府将于 2020 年重点关注这一主题,特别是数字医疗合作对进步的核心地位,但 COVID-19 大流行的前所未有的影响清楚地表明,迫切需要了解数据的重要性及其对决策的解释制作。随着加拿大和世界各地解决从人口和资源的高层政策到患者结果的日常预测分析等各种问题,信息学和计算科学方面的熟练劳动力准备以及健康数据及其应用的必要背景至关重要。当前疫情大流行的一线希望可能在于加拿大正在投资资源,以准备我们的集体应对措施,这在数据的帮助下至关重要。虽然人工智能和信息学在快速分析下一代大规模数据方面显示出巨大的前景,但由于健康数据的独特性,未来的工作人员将需要高度专业化的培训。加拿大信息和通信技术委员会预计,到 2023 年,需要超过 30 万名具有计算科学专业知识的技术工人。其中,超过 12 万名将为健康和生物技术做出贡献,这是未来经济的六个创新领域之一。为了在新的就业市场中打造成功的职业生涯,我们的 CREATE 计划中的 HQP 不仅将学习最先进的计算和信息学,而且还将培养对健康数据背景的深度和广度的理解以及使他们能够灵活地使用方法在如此快速变化的环境中保持最新状态。我们与医疗信息学领域的主要利益相关者合作,并通过问题解决、体验式学习和专业成长方面的创新来补充技术培训。为了巩固加拿大在全球领域的竞争优势,我们共同努力培养具有多学科经验的计算机科学家,并吸引包括妇女、黑人和土著社区、受过国际教育的专业人员、职业转型者和残疾人等不同群体的参与。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Mousavi, Parvin其他文献
iPINBPA: an integrative network-based functional module discovery tool for genome-wide association studies.
iPINBPA:一种基于网络的综合功能模块发现工具,用于全基因组关联研究。
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Wang, Lili;Mousavi, Parvin;Baranzini, Sergio E - 通讯作者:
Baranzini, Sergio E
Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection.
从 RF 到 B 模式时间增强超声特征的迁移学习,用于前列腺癌检测。
- DOI:
- 发表时间:
2017-07 - 期刊:
- 影响因子:0
- 作者:
Azizi, Shekoofeh;Mousavi, Parvin;Yan, Pingkun;Tahmasebi, Amir;Kwak, Jin Tae;Xu, Sheng;Turkbey, Baris;Choyke, Peter;Pinto, Peter;Wood, Bradford;Abolmaesumi, Purang - 通讯作者:
Abolmaesumi, Purang
A user-driven machine learning approach for RNA-based sample discrimination and hierarchical classification
一种用户驱动的机器学习方法,用于基于 RNA 的样本区分和层次分类
- DOI:
10.1016/j.xpro.2023.102661 - 发表时间:
2023-10-31 - 期刊:
- 影响因子:0
- 作者:
Imtiaz, Tashifa;Nanayakkara, Jina;Fang, Alexis;Jomaa, Danny;Mayotte, Harrison;Damiani, Simona;Javed, Fiza;Jones, Tristan;Kaczmarek, Emily;Adebayo, Flourish Omolara;Imtiaz, Uroosa;Li, Yiheng;Zhang, Richard;Mousavi, Parvin;Renwick, Neil;Tyryshkin, Kathrin - 通讯作者:
Tyryshkin, Kathrin
Computer-aided diagnosis of prostate cancer with emphasis on ultrasound-based approaches: A review
- DOI:
10.1016/j.ultrasmedbio.2007.01.008 - 发表时间:
2007-07-01 - 期刊:
- 影响因子:2.9
- 作者:
Moradi, Mehdi;Mousavi, Parvin;Abolmaesumi, Purang - 通讯作者:
Abolmaesumi, Purang
Open Source Platform for Transperineal In-Bore MRI-Guided Targeted Prostate Biopsy.
用于经会阴腔内 MRI 引导的靶向前列腺活检的开源平台。
- DOI:
- 发表时间:
2020-02 - 期刊:
- 影响因子:0
- 作者:
Herz, Christian;MacNeil, Kyle;Behringer, Peter A;Tokuda, Junichi;Mehrtash, Alireza;Mousavi, Parvin;Kikinis, Ron;Fennessy, Fiona M;Tempany, Clare M;Tuncali, Kemal;Fedorov, Andriy - 通讯作者:
Fedorov, Andriy
Mousavi, Parvin的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Mousavi, Parvin', 18)}}的其他基金
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2021
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2021
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2020
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Health Research Projects
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2020
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2020
- 资助金额:
$ 10.79万 - 项目类别:
Discovery Grants Program - Individual
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2020
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Health Research Projects
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2019
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Health Research Projects
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2019
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Health Research Projects
相似国自然基金
下肢外骨骼机器人康复训练过程中人体多参数生物演变机理和定量化评估方法研究
- 批准号:52365039
- 批准年份:2023
- 资助金额:32 万元
- 项目类别:地区科学基金项目
有氧训练减轻DAP3/MBNL1/PKM2信号轴依赖的糖酵解改善DM1肌肉萎缩的机制研究
- 批准号:82302850
- 批准年份:2023
- 资助金额:30 万元
- 项目类别:青年科学基金项目
大规模基因预训练模型及其在基因结构与功能研究中的应用
- 批准号:62372098
- 批准年份:2023
- 资助金额:50 万元
- 项目类别:面上项目
基于预训练深度生成模型的相互作用蛋白质设计关键技术及应用研究
- 批准号:62306334
- 批准年份:2023
- 资助金额:30 万元
- 项目类别:青年科学基金项目
基于Metrnl介导的AMPK/mTOR/ULK1通路探讨舌肌训练对老年OSA患者的治疗作用及相关机制研究
- 批准号:82370093
- 批准年份:2023
- 资助金额:49 万元
- 项目类别:面上项目
相似海外基金
NSERC CREATE Training Program for Controlled Release Leaders (ContRoL)
NSERC CREATE 控释领导者培训计划 (ContRoL)
- 批准号:
555324-2021 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Research and Training Experience
NSERC CREATE for the Wearable Technology Research and Collaboration (We-TRAC) training program
NSERC CREATE 可穿戴技术研究与合作 (We-TRAC) 培训计划
- 批准号:
511166-2018 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Research and Training Experience
NSERC CREATE for the Wearable Technology Research and Collaboration (We-TRAC) training program
NSERC CREATE 可穿戴技术研究与合作 (We-TRAC) 培训计划
- 批准号:
511166-2018 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Research and Training Experience
PRoTECT - Plant Responses To Eliminate Critical Threats: An NSERC-CREATE-DFG-IRTG joint training program to train the next generation of "Plant Doctors"
PROTECT - 消除严重威胁的植物反应:NSERC-CREATE-DFG-IRTG 联合培训计划,旨在培训下一代“植物医生”
- 批准号:
509257-2018 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Research and Training Experience
CREATE Training Program in Medical Informatics: Preparing Canada's Workforce for Health Data of Tomorrow
创建医疗信息学培训计划:让加拿大劳动力为明天的健康数据做好准备
- 批准号:
555366-2021 - 财政年份:2022
- 资助金额:
$ 10.79万 - 项目类别:
Collaborative Research and Training Experience