At Howard University, engineers, clinicians, and data scientists are collaborating to expand cancer research through imaging, chemistry, and artificial intelligence.
This week, Howard University announced that a medical physicist, an associate professor of chemistry, and an assistant professor in the College of Engineering and Architecture are conducting research supported by grants.
These include a U54 pilot grant through the Howard University-Johns Hopkins University partnership and funding for artificial intelligence data sharing systems.
Kofi Deh, assistant professor of physics and astronomy, develops advanced MRI and artificial intelligence tools to enhance cancer detection and expand access to innovative imaging technologies.
His research includes MRI techniques that probe tumor biology beyond conventional scans and methods that enable hospitals to improve AI models collaboratively without sharing sensitive patient data.
Jacqueline Smith, associate professor of chemistry, leads research on targeted cancer therapies that attack tumors while minimizing harm to healthy cells.
She manages the Smith Research Lab, a recipient of two National Science Foundation grants.
Current projects include developing small molecules to target cancer cells, drug delivery systems that use cancer cell surface proteins to guide therapies, and trackable molecules to confirm drug delivery. Smith is seeking funding from the American Cancer Society and the American Association for Cancer Research, with the long-term goal of securing a National Institutes of Health R01 grant to expand her lab.
Engineers, clinicians, and data scientists are collaborating to expand cancer research through imaging, chemistry, and AI.
Anietie Andy, assistant professor of electrical engineering and computer science, develops AI systems that integrate medical records, imaging, and clinical data to improve cancer prediction and care.
He helped establish the Howard University AI in Healthcare initiative to foster collaboration among clinicians, engineers, and data scientists.
Andy also directs the Howard University Natural Language Processing Group.
His research focuses on developing AI models that combine medical data, imaging, lab results, and clinical notes to improve cancer risk prediction, particularly for breast and colon cancer.
This work is being developed into a National Institutes of Health R01 proposal.