Medical Imaging Informatics Training Grant

医学影像信息学培训补助金

• 批准号: 10254253
• 负责人: ALEX BUI
• 金额: $ 18.33万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10254253
• 关键词: Grant; Medical Imaging; informatics training

ABSTRACT (PROJECT DESCRIPTION) With the “digital era of biomedicine” upon us, exciting opportunities arise to revolutionize how we perform scien- tific research and deliver healthcare. Burgeoning areas like precision medicine foreshadow a transformation of how we understand disease and its individually-tailored treatment. In this context, the importance of imaging continues to grow, both as a driver of new knowledge and as a vital tool which uses these insights towards better detection, diagnosis, and treatment for patients. But achieving the full promise of this future still requires over- coming many barriers, and new imaging informaticians must be equipped with the cutting-edge skills that will create and support the necessary computational advances and methods. The UCLA Medical Imaging Informatics (MII) training program aims to be a leader in training this next generation of imaging informaticians who will develop the needed computational approaches and applications that enable this future. Bringing together leading experts from across our institution in imaging, engineering (computer and data science, electrical, bioengineering), (bio)statistics, and medicine, MII envisions an environment fostering interdisciplinary teaching and mentoring of students; and promoting innovative research throughout the spectrum of imaging informatics. MII's training program involves a comprehensive 1-year core curriculum introducing foun- dational principles of the discipline, forming a breadth of understanding while reinforcing the technical proficien- cies needed by any imaging informatician. Students complete coursework covering topics presented from the perspective of medical imaging and healthcare, including: information architectures; data and knowledge repre- sentation; data mining; machine learning; biostatistics; and information retrieval. Cross-cutting topics (e.g., radi- ogenomics, multimodal data integration and biomarker development) are presented throughout these courses. In parallel to the core curriculum, students are immediately engaged in research, completing rotations with faculty to gain an appreciation for contemporary imaging informatics projects. With this experience, PhD students sub- sequently specialize via more advanced elective coursework customized to their particular research interests. Students are challenged to propose, develop, and test new imaging informatics methods that will advance the discipline, as well as ultimately change and affect healthcare. Importantly, both training and research are inter- woven within a biomedical application domain and with appropriate PhD and MD mentorship to ensure compu- tational/informatics, clinical, and real-world translational insights and guidance. Recognizing the evolving land- scape of the biomedical workforce, our T32 includes a number of professional development activities, including internships, providing practical (research) experiences in different settings. Through the experiences gained dur- ing this T32 training program, MII students will become independent scientists, prepared to contribute to and lead imaging informatics as it continues to grow.

摘要（项目描述） 随着“生物医学数字时代”的到来，令人兴奋的机会出现，彻底改变我们的科学研究方式。 专门研究并提供医疗保健。精准医学等新兴领域预示着一场变革 我们如何理解疾病及其量身定制的治疗方法。在此背景下，影像学的重要性 持续增长，既作为新知识的驱动力，又作为利用这些见解更好地发展的重要工具 为患者提供检测、诊断和治疗。但要实现这个未来的全部承诺仍然需要 即将到来的许多障碍，新的成像信息学家必须具备尖端技能， 创建并支持必要的计算进步和方法。 加州大学洛杉矶分校医学影像信息学 (MII) 培训计划旨在成为培训下一代的领导者 成像信息学家将开发所需的计算方法和应用程序，使 这个未来。汇集了我们机构在成像、工程（计算机和 数据科学、电气、生物工程）、（生物）统计学和医学，MII 设想了一个培育环境 跨学科教学和学生指导；并促进整个领域的创新研究 的影像信息学。 MII 的培训计划包括为期 1 年的综合核心课程，介绍基础知识 学科的基本原则，形成广泛的理解，同时加强技术熟练程度 任何成像信息学家都需要的信息。学生完成涵盖主题的课程作业 医学影像和医疗保健的视角，包括：信息架构；数据和知识表示 感觉；数据挖掘；机器学习；生物统计学；和信息检索。跨领域主题（例如，辐射 基因组学、多模式数据集成和生物标志物开发）在这些课程中都有介绍。 在核心课程的同时，学生立即参与研究，完成与教师的轮换 了解当代成像信息学项目。有了这些经验，博士生们 随后通过根据其特定研究兴趣定制的更高级的选修课程进行专业化。 学生面临的挑战是提出、开发和测试新的成像信息学方法，以推进 纪律，并最终改变和影响医疗保健。重要的是，培训和研究都是相互的 编织在生物医学应用领域，并有适当的博士和医学博士指导，以确保计算 国家/信息学、临床和现实世界的转化见解和指导。认识不断变化的土地 生物医学劳动力的景观，我们的 T32 包括许多专业发展活动，包括 实习，在不同环境中提供实践（研究）经验。通过期间获得的经验 通过这个 T32 培训计划，信息产业部的学生将成为独立科学家，准备为以下领域做出贡献： 引领成像信息学的不断发展。