With the use of artificial intelligence tools rising, more people have become interested in using them to better our daily lives. However, the use of these tools could become even more significant than we expect. Stevens Professor Yu Gan is looking forward to developing algorithms that can help doctors accurately detect diseases and find patterns in medical data. As a result, there’s a positive outlook in using artificial intelligence to bring technological breakthroughs.
Gan’s journey began when he realized that people “could use algorithms to enhance images, unveil clinical info and improve people’s health and their quality of life.” He received his Ph.D. in electrical engineering at Columbia University, and joined the University of Alabama as a faculty member before joining Stevens in the fall of 2022. Although his work has recently focused on the internal imaging of the heart’s arteries, Gan has been working with other professionals and his students to create deep learning algorithms that can each analyze specific medical images and assist in treating patients.
At Stevens’ McClean Hall, two imaging systems—a low-quality system, and a high-quality system—are being used along with a Lambda GPU workstation to find detection patterns for healthy and unhealthy arteries. Stevens graduate students also help improve the algorithm that is analyzing the images to become more precise. The main focus of the software is for it to highlight artery clogging patterns that physicians would not usually pick up on. With these efforts, doctors would be able to back up their patients’ diagnoses and prevent any errors.
Additionally, the German Cancer Research Center (DKFZ) has been receiving support from Gan’s lab to uncover the dynamics of cancer cells. This is done through the student team’s artificial intelligence software, which is able to analyze a collection of tumor cells. In fact, the lab’s Matlab program was used in the research center’s facilities for studying cell response in cancer cells. The program uses individual color channels to plot the intensity of images for processing. Favorably, such algorithms are accessible to the public and can help with other projects, while being privately funded and looking for more support.
Outside of the specialized medical fields, Gan hopes to bring an application that can be used regularly by smartphone users. The idea is to have an app that can evaluate food through a millimeter-wage image of it, while using the frequency of a 5G smartphone. Additionally, the project has received funding from the USDA National Institute of Food and Agriculture to proceed with it. This task would be inexpensive while bringing about new safety precautions when buying foods. Currently, Gan and his team use microwave images of foods, but with more development, the Stevens researchers could possibly create a system that can help diagnose skin cancer.
Artificial intelligence tools have given researchers and students new opportunities to create technology that can change the way that people will see what is in front of them. The outlook of these tools is to give people new ways of examining things and tackle challenges while gaining new information. As expectations are for programs to be able to handle even larger quantities of data, present and previous knowledge can create more accurate standards of analysis.
Professor Yu Gan’s studies have demonstrated the unique implementation of machine learning, bringing about a research area that has not had much development. As a result, the Machine Learning in Biomedical Engineering graduate-level class was created at Stevens so more students can explore. As projects become more specialized, interconnectedness can be found between fields and broaden the possibilities of new ideas. As a result, there is great potential for more to be uncovered through new investigative methods.
