As incidence rates of cancer rise, pathology reports are generated at a similar pace. The processing must be completed manually because of variation among these reports. This activity is time-consuming and costly.

In the Community College Internship (CCI) program at Oak Ridge National Laboratory (ORNL), computer science student Thy Pham contributed to a project dedicated to automating the classification of these reports. Pathology reports detail the diagnosis determined from the examination of cells and tissues under a microscope. The suppliers of diagnostic reports often use variants of the same term in a diagnosis, sometimes leading to confusion when classifying the reports.

ORNL Undergraduate Research Profile: Thy Pham

Computer science student Thy Pham used deep learning techniques to help automate the classification of pathology reports in the Community College Internship program at Oak Ridge National Laboratory.

Under the guidance of Hong-Jun Yoon, Ph.D., Pham assisted with research on natural language processing using deep learning. Ultimately, the team’s goal is to increase classification accuracy and improve the reliability of the automation module.

“The extraction of clinical info from medical text is an important problem in the medical domain, but it requires well-trained human labor, which is costly,” Pham said. “The purpose of this study is to automate this procedure to achieve info extraction in a timely manner so we can perform further analysis about cancer epidemiology.”

Pham has always been interested in the capabilities of technology, something she realized while participating in programming competitions and a STEM club in high school. This interest led her to pursue computer science and engineering at Orange Coast College and to seek additional opportunities.

“While researching, ORNL seemed like the perfect place for professional growth,” Pham said. “Its history, emphasis on building greater technologies and powerful facilities that contribute to energy efficiency are among the many attractions that led me here.”

Pham improve her technical skills related to machine learning and she expanded her outlook. The research process taught her to disregard scenarios beyond her control and to remain patient while waiting for results. Additionally, she learned to search for the larger picture instead of focusing on insignificant details.

After participating in the CCI program, Pham plans to complete her associate degree and enroll in a four-year institution. Someday, she hopes to form her own technology company dedicated to improving the environmental safety and living conditions of the world’s population.

Pham would like to mentor and share her knowledge of machine learning with students at her former high school STEM club.

“I believe that this program was the starting point of a future successful career,” Pham said. “When it comes to the specifics of what I want to achieve and the ways I can get there, this internship revealed paths that were not visible to me before.”

The CCI program is sponsored by the U.S. Department of Energy Office of Science’s Office of Workforce Development for Teachers and Scientists (WDTS) and is administered by the Oak Ridge Institute for Science and Education (ORISE), managed by ORAU.