) 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.

Public Health Relevance

The UCLA Medical Imaging Informatics (MII) training program aims to train and inspire a new generation of imaging informaticians who will lead the development of innovative approaches that inform and enable precision medicine. MII establishes a cross-campus, interdisciplinary environment to teach and mentor future scientists in cutting-edge computational and data science methods towards imaging; and creates novel, team science re- search opportunities in which graduate students work and learn from leading experts in the field. MII trainees are exposed to the breadth of contemporary imaging informatics research, and are ultimately prepared to be productive, independent scientists that will participate in shaping the discipline as biomedical research and healthcare evolve.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Institutional National Research Service Award (T32)
Project #
5T32EB016640-08
Application #
10006830
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Erim, Zeynep
Project Start
2013-09-01
Project End
2023-08-31
Budget Start
2020-09-01
Budget End
2021-08-31
Support Year
8
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California Los Angeles
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
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