Medical Imaging Informatics Training Program
Medical Imaging Informatics Training Program
批准号:
8094394
负责人:
ALEX BUI
金额:
$52.58万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-07-01 至 2013-06-30
关键词:
ArchitectureAreaBioinformaticsBiomedical EngineeringClinical ResearchDataDecision MakingDevelopmentDisciplineDoctor of PhilosophyEducational CurriculumEngineeringFacultyGenerationsGrantImageInformaticsInformation SciencesInvestigationKnowledge DiscoveryLettersMedicalMedical ImagingMedical InformaticsMedicineMethodsResearchResearch PersonnelRetrievalScientistStandardizationStressStudentsTrainingTraining ProgramsTraining SupportTranslational ResearchWorkbasebiomedical informaticscomputer sciencefundamental researchhuman diseaseimaging informaticsin vivoinformatics traininginformation organizationinnovationinsightinterestmedical schoolsnovelpost-doctoral trainingprogramsstatisticstheories
中文摘要
描述(由申请人提供):
这笔赠款的目的是支持对即将到来的一代科学家进行医学成像信息学方面的培训。生物医学信息学的下一个重大挑战将是支持新的知识发现:因此,该培训计划的应用领域将是支持临床和翻译研究的信息学。除了现有的信息学研究外,还需要一系列学科(计算机科学、应用数学、统计学、医学)的基础理论和发展来促进这种信息学研究,并必须将其整合到前瞻性培训计划中。该计划进一步侧重于成像信息学:随着成像作为客观记录和理解人类疾病的体内方法的普遍使用,在获取、理解和使用此类数据以创造新的洞察力方面出现了新的和独特的研究挑战。
博士(PhD)和博士后培训是在目前加州大学洛杉矶分校(UCLA)基于成像的医学信息学NLM培训资助的基础上发展起来的,通过加州大学洛杉矶分校生物医学工程跨部门计划批准的医学成像信息学学位授予轨道提供博士(PhD)和博士后培训。该课程包括一个为期一年的综合核心课程,提供对生物医学信息学(医学数据标准和信息架构;知识表示;医疗决策;信息提取/检索;生物信息学)以及医学图像获取、标准化和内容理解的基本原则的广泛理解。进一步的专业化是通过随后的选修课实现的,这些选修课提供特定信息领域的专业知识。重要的是,该计划强调信息学研究及其后续
申请,要求学员进行新颖和创新的调查,作为课程的一部分
学习。核心教师来自加州大学洛杉矶分校医学院、工程学院、文学与科学学院和信息研究学院的跨学科研究小组。该项目将能够利用其核心教师和整个加州大学洛杉矶分校的广泛的生物医学和信息学努力,为学生提供大量的研究机会。此外,该培训计划将支持本科生的短期暑期培训,以鼓励他们对生物医学和成像信息学研究生工作的兴趣。
英文摘要
DESCRIPTION (provided by applicant):
The objective of this grant is to support training of the upcoming generation of scientists in medical imaging informatics. The next significant challenge in biomedical informatics will be to support new knowledge discovery: thus, the application domain of this training program will be on informatics in support of clinical and translational research. In addition to existing informatics research, fundamental theories and developments from a spectrum of disciplines (computer science, applied math, statistics, medicine) will be required to facilitate such informatics research, and must be integrated into a forward-looking training program. This program further focuses on imaging informatics: with the now ubiquitous usage of imaging as an in vivo method for objectively documenting and understanding human disease, new and unique research challenges arise in the acquisition, the understanding, and the usage of such data towards creating novel insights.
Evolving from the current UCLA NLM training grant in imaging-based medical informatics, doctoral (PhD) and postdoctoral training are offered through an approved degree-granting track in medical imaging informatics in the UCLA Biomedical Engineering Interdepartmental Program. The program consists of a comprehensive one year core curriculum that provides a breadth of understanding in biomedical informatics (medical data standards and information architectures; knowledge representation; medical decision making; information extraction/ retrieval; bioinformatics) and the underlying principles of medical image acquisition, standardization, and content understanding. Further specialization is achieved through subsequent elective courses that provide expertise in a given informatics area. Importantly, the program stresses informatics research and its subsequent
application, requiring trainees to conduct novel and innovative investigations as part of the course of
study. Core faculty are drawn from an interdisciplinary group of researchers in the UCLA Schools of Medicine, Engineering, Letters & Sciences, and Information Studies. This program will be able to leverage the wide array of biomedical and informatics endeavors from its core faculty and across the UCLA campus to provide students with numerous opportunities for research. Additionally, this training program will support short-term summer training for undergraduate students to encourage interest in biomedical and imaging informatics graduate work.
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DOI:
10.1109/hisb.2012.10
发表时间:
2012-09
期刊:
Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology
影响因子:
--
作者:
[Suh MK, Woodbridge J, Moin T, Lan M, Alshurafa N, Samy L, Mortazavi B, Ghasemzadeh H, Bui A, Ahmadi S, Sarrafzadeh M]
通讯作者:
Sarrafzadeh M
DOI:
10.1016/j.pmcj.2015.09.006
发表时间:
2016-06
期刊:
Pervasive and mobile computing
影响因子:
4.3
作者:
[Woodbridge J, Mortazavi B, Bui AA, Sarrafzadeh M]
通讯作者:
Sarrafzadeh M
Natural language processing with dynamic classification improves P300 speller accuracy and bit rate.
DOI:
10.1088/1741-2560/9/1/016004
发表时间:
2012-02
期刊:
Journal of neural engineering
影响因子:
4
作者:
[Speier W, Arnold C, Lu J, Taira RK, Pouratian N]
通讯作者:
Pouratian N
DOI:
10.1109/bhi.2016.7455931
发表时间:
2016-02
期刊:
... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics
影响因子:
--
作者:
[Garcia-Gathright JI, Matiasz NJ, Garon EB, Aberle DR, Taira RK, Bui AAT]
通讯作者:
Bui AAT
DOI:
10.1109/tbcas.2011.2166073
发表时间:
2012-04
期刊:
IEEE transactions on biomedical circuits and systems
影响因子:
5.1
作者:
[Au LK, Bui AA, Batalin MA, Kaiser WJ]
通讯作者:
Kaiser WJ
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