As research in healthcare grows, the amount of data also increases dramatically and becomes harder to manage. Through this partnership, our co-director, Dr. Daniel Chow, believes having a partner such as Syntropy to help manage the centralization and integration of healthcare data will prove to be vital in UCI's research efforts to continue driving innovative changes to our patients.

Michelle Bardis, MD, a resident at UCI, under her RSNA Research Medical Student Grant, “Prostate Cancer Detection, Quantification, and Characterization with Artificial Intelligence,” trained a 3D2D U-Net to segment the two prostate zones within T2 prostate MRIs. These results show that by being able to accurately segment these zones, this can assist the PI-RADS scoring system to accurately identify in which zone the lesion is in.

Dr. Peter Chang was nominated as Most Influential Radiology Researcher in the 2021 Edition of the Minnies for AuntMinnie.com The Best of Radiology.

The UC Irvine Precision Health through Artificial Intelligence Initiative (PHAI) is soliciting applications for a total of two research seed grants leveraging machine and novel computational approaches to advance patient care. Priority is given to projects that leverage existing UCI Resources Cores including the Center for Artificial Intelligence and Diagnostic Medicine (CAIDM) and Genomics High-Throughput Facility (GHTF).

UCI Health has created a system for delivering monoclonal antibodies to save the amount of hospital beds needed for COVID-19 patients. Read more to learn about how this model accelerates the treatment speed of monoclonal antibodies and how AI technology is integrated to treat COVID-19.

UCI is hosting the Second Annual University of California Artificial Intelligence in Radiology conference for 2020. UC investigators across five UC academic centers will present their groundbreaking research and discuss deployment of AI tools in a clinical setting. The video recording can be accessed by clicking the image.

Read about Dr. Chang and Dr. Chow's contributions to an AI tool for identifying risk of COVID-19 complications on page 9 of the October RSNA News.

Neuroradiologists Peter D. Chang, MD, and Daniel S. Chow, MD, were on a team that developed an AI tool, or vulnerability scoring machine, using machine learning (ML) to calculate the likelihood that a COVID-19 patient will need a ventilator or some form of escalated care.

Watch the linked video to see the presentation for the CAIDM's manuscript accepted by the American Journal of Roentgenology. The paper introduces a hybrid 3D/2D CNN network for prostate segmentation.