The Academic Minute

How do you get kids to learn to listen?  Use music. Gena Greher, professor of music and music education at the University of Massachusetts, Lowell, shows us how. Dr. Gena R. Greher is Professor of Music & Music Education at the University of Massachusetts Lowell. She’s a 2014_15 Donahue Endowed Professor of the Arts. and […]

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Sharing is caring. Nicole Hassoun, professor of philosophy at Binghamton University, examines global health through the lens of fighting off the next contagious virus. Hassoun is the director of the Global Health Impact (GHI), which works to create positive change by evaluating pharmaceutical products’ global health consequences and advocating for greater access to essential medicines. To learn more about this project […]

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Solving big challenges in our society demands working together as a team. Luisa Ruge-Jones, assistant professor of communication at the University of Dayton, explores the best way to do this. Luisa Ruge-Jones’ primary research interests focus on team science, group communication and organizational communication. Her research examines how organizational policies and infrastructure affect how teams […]

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How do you know if you’re getting too much sun exposure? Stephen McNeill, senior lecturer of communication at Kennesaw State University, examines one technology that can help. Before embarking on a career in academics, McNeill worked as an on-air personality for multiple radio stations in the U.S. and the U.K. and appeared on television shows […]

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How can researchers compare findings if not everyone is on the same page? Cailyn Green, assistant professor of addiction studies at Empire State University, examines the health effects of teen substance use. Cailyn Green, MS, Ph.D., CASAC is the Assistant Professor of Addiction Studies at the State University of New York, Empire State College. She […]

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On this Student Spotlight during University of California, Irvine Week:  Reducing carbon from transportation is key to our future. Candelaria Bergero, Ph. D. student in Earth system science, examines how to cut emissions from one form of transport. Candelaria Bergero is a Ph.D. student in Earth System science at the University of California, Irvine. She […]

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On University of California, Irvine Week:  Knowing who gets vaccinated more often, can tell us whom to target in future vaccine efforts. Keri Hurley-Kim, associate clinical professor in the School of Pharmacy & Pharmaceutical Sciences, looks into the data. Dr. Hurley is a pharmacy educator and has worked with PharmD students and residents at all […]

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On University of California, Irvine Week:  We hear about the harm bacteria can do, but what about the good? Regina Ragan, professor of materials science and engineering, examines this question. Ragan is a recipient of the National Science Foundation Faculty Early CAREER Award and a Fulbright Fellow. She is co-Director of the Institute for Design […]

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On University of California, Irvine Week: Racial disparities can exist even in machine learning.

Jung In Park, assistant professor in the Sue & Bill Gross School of Nursing, finds a way to tackle biases and make a difference for vulnerable populations.

Faculty Bio:

Dr. Jung In Park is an assistant professor at UCI’s school of nursing since joining in 2019. Her research area focuses on biomedical informatics using large datasets and AI/machine learning approaches to provide scientific evidence for predicting patient outcomes. Prior to UCI, Dr. Park was a postdoctoral Scholar at Stanford University in Biomedical Informatics. Dr. Park received her Ph.D. from the University of Minnesota in Nursing Informatics and her B.S. from Seoul National University in Nursing.

Transcript:

Survival machine learning is widely accepted as a useful approach for forecasting future events. But there is one caveat – machine learning models can potentially create racial disparities through the data used to train them.

In healthcare, machine learning can be used to predict the survival outcomes of patients, which is a critical component of treatment. Determining survival outcomes helps practitioners determine proper treatment options and appropriate cancer care.

My team and I conducted this study to develop race and ethnicity-specific survival machine learning models for Hispanic and Black women diagnosed with breast cancer. The goal of this study was to examine whether race and ethnicity-specific machine learning models outperform the general model trained with all race and ethnicity data.

Using the data from the National Cancer Institute’s cancer registries, we were able to develop the Hispanic-specific and Black-specific models and compare them with the general model using the Cox proportional-hazards model, Gradient Boost Tree, survival tree and survival support vector machines.

After analyzing the results, we identified over 300,000 female patients who had breast cancer diagnoses between 2000 and 2017. When comparing the race and ethnicity specific models to the general model we found that Hispanic and Black women models outperformed when predicting the outcomes of specific race and ethnicity.

Predicting the individualized survival outcomes of breast cancer patients can further provide the evidence needed for identifying treatment options and high-quality cancer care for minority populations. Additionally, race and ethnicity-specific machine learning models can help tackle representation bias and contribute to mitigating health disparities.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.academicminute.org

On University of California, Irvine Week:  Racial disparities can exist even in machine learning. Jung In Park, assistant professor in the Sue & Bill Gross School of Nursing, finds a way to tackle biases and make a difference for vulnerable populations. Dr. Jung In Park is an assistant professor at UCI’s school of nursing since joining […]