# Medical Imaging Informatics Training Grant

> **NIH NIH T32** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $175,095

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10006830
- **Project number:** 5T32EB016640-08
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** ALEX BUI
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $175,095
- **Award type:** 5
- **Project period:** 2013-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006830

## Citation

> US National Institutes of Health, RePORTER application 10006830, Medical Imaging Informatics Training Grant (5T32EB016640-08). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10006830. Licensed CC0.

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