- The University of California, Irvine (UCI) and UCI Health System have launched the UCI Center for Artificial Intelligence in Diagnostic Medicine, which will leverage machine learning tools in all areas of clinical care to improve outcomes and lower costs.
Peter D. Chang, MD and Daniel S. Chow, MD, neuroradiologists in the Department of Radiological Sciences at UCI School of Medicine, will lead the center. The team will focus on developing deep learning neural networks and applying them to diagnostics, disease prediction, and treatment planning.
The new facility will also allow all UCI faculty, students, and researchers to collaborate and translate AI-based concepts into clinical tools that will improve individual and population health.
“Our goal is to empower healthcare providers, researchers and patients through the use of artificial intelligence in healthcare,” said Chang.
The center will build on research conducted by Chang and Chow, who recently designed an AI-driven “virtual biopsy” technique to evaluate genetic mutations in brain tumors.
The tool achieved diagnostic accuracy of 94 percent, identifying relevant genetic mutations in patients with either high- or low-grade brain tumors.
The study showed the potential for convolutional neural networks to detect image details without human direction.
Chang, Chow and their colleagues also recently developed a customized deep learning algorithm that detected brain hemorrhage on non-contrast CT head exams with more than 97 percent accuracy.
Researchers applied the deep learning tool to more than 10,000 UCI Health imaging exams to test its efficiency, and validated the algorithm using prospective data.
The study involved the detection and quantification of brain bleeds, including intracranial hemorrhages.
“Intracranial hemorrhages are significant medical emergencies that result in 40 percent patient mortality, despite aggressive care,” said Chang.
“Early and accurate diagnosis is necessary for the management of life-threatening brain bleeds and to improve the odds of recovery.”
The Center for Artificial Intelligence is now preparing the deep learning algorithm for clinical use in the UCI Medical Center emergency department.
“The research is an example of how we can use machine learning technology to improve the delivery of acute care in an emergency department by expediting triage of patient care and offering more detailed information to guide clinical decision making,” said Chow.
“An AI-based imaging may be used either as a triage system to assist radiologists in identifying high-priority exams for interpretation or as a method to rapidly quantify ICH volume, or both.”