Following the people and events that make up the research community at Duke

Students exploring the Innovation Co-Lab

Author: Victoria Wilson

Student Researchers Share What They Know About AI and Health

The healthcare industry and academic medicine are excited about the potential for artificial intelligence — really clever computers — to make our care better and more efficient.

The students from Duke’s Health Data Science (HDS) and AI Health Data Science Fellowship who presented their work at the 2022 Duke AI Health Poster Showcase on Dec. 6 did an excellent job explaining their research findings to someone like me, who knows very little about artificial intelligence and how it works. Here’s what I learned:

Artificial intelligence is a way of training computer systems to complete complex tasks that ordinarily require human thinking, like visual categorization, language translation, and decision-making. Several different forms of artificial intelligence were presented that do healthcare-related things like sorting images of kidney cells, measuring the angles of a joint, or classifying brain injury in CT scans.

Talking to the researchers made it clear that this technology is mainly intended to be supplemental to experts by saving them time or providing clinical decision support.

Meet Researcher Akhil Ambekar

Akhil standing next to his poster “Glomerular Segmentation and Classification Pipeline Using NEPTUNE Whole Slide Images”

Akhil Ambekar and team developed a pipeline to automate the classification of glomerulosclerosis, or scarring of the filtering part of the kidneys, using microscopic biopsy images. Conventionally, this kind of classification is done by a pathologist. It is time-consuming and limited in terms of accuracy and reproducibility of observations. This AI model was trained by providing it with many questions and corresponding answers so that it could learn how to correctly answer questions. A real pathologist oversaw this work, ensuring that the computer’s training was accurate.

Akil’s findings suggest that this is a feasible approach for machine classification of glomerulosclerosis. I asked him how this research might be used in medicine and learned that a program like this could save expert pathologists a lot of time.

What was Akhil’s favorite part of this project? Engaging in research, experimenting with Python and running different models, trying to find what works best.

Meet Researcher Irene Tanner

Irene Tanner and her poster, “Developing a Deep Learning Pipeline to Measure the Hip-Knee-Ankle Angle in Full Leg Radiographs”

The research Irene Tanner and her team have done aims to develop a deep learning-based pipeline to calculate hip-knee-ankle angles from full leg x-rays. This work is currently in progress, but preliminary results suggest the model can precisely identify points needed to calculate the angles of hip to knee to ankle. In the future, this algorithm could be applied to predict outcomes like pain and physical function after a patient has a joint replacement surgery.

What was Irene’s favorite part of this project? Developing a relationship with mentor, Dr. Maggie Horn, who she said provided endless support whenever help was needed.

Meet Researcher Brian Lerner

Brian Lerner and his poster, “Using Deep Learning to Classify Traumatic Brain Injury in CT Scans”

Brian Lerner and his team investigated the application of deep learning to standardize and sharpen diagnoses of traumatic brain injury (TBI) from Computerized Tomography (CT) scans of the brain. Preliminary findings suggest that the model used (simple slice) is likely not sufficient to capture the patterns in the data. However, future directions for this work might examine how the model could be improved. Through this project, Brian had the opportunity to shadow a neurologist in the ER and speculated upon many possibilities for the use of this research in the field.

What was Brian’s favorite part of this project? Shadowing neurosurgeon Dr. Syed Adil at Duke Hospital and learning what the real-world needs for this science are.

Many congratulations to all who presented at this year’s AI Health Poster Showcase, including the many not featured in this article. A big thanks for helping me to learn about how AI Health research might be transformative in answering difficult problems in medicine and population health.

By Victoria Wilson, Class of 2023

Cancer Stigma, Contraceptives, Covid-19: 2022 Global Health Research Showcase

Last Monday, Oct. 17, Duke University students who had conducted global health research had the opportunity to present their work. From North Carolina to Sub-Saharan Africa, the 2022 Global Health Research Showcase featured works that tackle some of the world’s most pressing health issues. Over 40 undergraduate, Masters, and PhD student projects examined a broad range of issues, determinants, and phenomena in countries from almost every continent. Here’s a few project highlights, in case you missed it:

Maeve Salm, pursuing her Master of Science in Global Health, went to Tanzania to study contraceptive use. Tanzania’s youth are highly impacted by teen pregnancy, and Salm wanted to understand desires for contraceptive use among adolescents affected by HIV. She learned that, much like in the U.S., stigma influences access to sexual healthcare for adolescents. This qualitative study aimed to support young people in achieving their desired health outcomes and reducing HIV transmission by examining barriers and facilitators to family planning. Findings indicate that youth agency in reproductive health is of utmost importance.

Maeve Salm presenting her poster at the 2022 Global Health Research Symposium.

Wondering about the Covid-19 response in other countries? Master of Science in Global Health Candidate Stephanie Stan explored the barriers and enablers to the pandemic response in Peru. Per capita, Peru experienced the highest mortality rate form the disease compared to any other country. Due to several challenging factors, they were slow to receive COVID-19 vaccines. However, they implemented highly successful vaccination campaigns once vaccines were obtained. What can be learned from Peru’s pandemic response? Prolonged and proactive collaborations between sectors (healthcare, academics, and government) enable swift public health responses in a crisis. It’s important to have elected officials who are empowered to make decisions promoting science.

“Definitely meeting all the incredible people that I interviewed and learning about their work and involvement in Peru’s pandemic response. Learning about what happens moving forward from their point of view.”

Stephanie Stan, when asked about her global health research experience

Winning the first-place Graduate Student Research Award, Judith Mwobobia’s project examined the stigma of cancer in sub-Saharan Africa. Stigma is a huge barrier to receiving treatment, which is a problem considering that 70% of global cancer deaths originate from Africa. Perceptions of financial stress, misconceptions about cancer, and fear of death were common attitudes driving cancer stigma. Proposed interventions included education and policy recommendations for low-resourced communities. Mwobobia is pursuing her Master of Science in Global Health. Clearly a supportive group, her classmates erupted in cheers when the award was announced.

By Victoria Wilson, Class of 2023

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