Artificial Intelligence Improves Prostate Cancer Detection
An important topic of discussion among radiologists is how artificial intelligence and machine learning, which recognize complex patterns in imaging data, will impact their field. John Onofrey, PhD, assistant professor of Radiology & Biomedical imaging and of Urology at Yale School of Medicine, is using those tools to augment the expertise of radiologists to improve the detection of prostate cancer.
James Duncan Discusses Big Data’s Role in Medical Imaging
Artificial intelligence and big data have long held promise for revolutionizing the field of medical imaging with their potential for faster and more accurate readings. As the technology continues to advance, the field of biomedical imaging is closer than ever to realizing those aims. James Duncan, the Ebenezer K. Hunt Professor of Biomedical Engineering, Electrical Engineering & Radiology and Biomedical Imaging, recently edited a special issue of Proceedings of the IEEE on this topic. We spoke with him about the role of computers in medical imaging, how they can work with humans, and how this can lead to improved health care.Source: School of Engineering & Applied Science
Yale Medicine Surgeons Use 3D Printing to Benefit Patients
Some Yale Medicine surgeons now routinely use 3D printing (essentially producing a solid, three-dimensional object from a virtual digital model) to plan surgeries, design tools specific to an upcoming surgery and that particular patient’s anatomy, and even to print some of the parts used to replace defective ones in the body.Source: Yale Medicine
John Onofrey, PhD joins Yale Urology as Assistant Professor
John Onofrey, PhD has been appointed an Assistant Professor of Urology and of Radiology & Biomedical Imaging, effective July 1, 2019. Dr. Onofrey begins this dual appointment after serving as Postdoctoral Associate and Associate Research Scientist in the Department of Radiology & Biomedical Imaging for the last six years.
Yale Researchers Propose a New Model for Neuroimaging Studies
For decades, two of the most precise imaging methods used to study the human brain, functional magnetic resonance imaging (fMRI) and Positron Emission Tomography (PET), have identified localized brain responses to sensory stimulation, such as touch, vision and smell.
Lower synaptic density is associated with depression severity and network alterations
Sophie Holmes, PhD, Associate Research Scientist, and Irina Esterlis, PhD, Associate Professor of Psychiatry, are the first and senior authors, respectively, of a study published in Nature Communications that examined synaptic density in 26 patients with major depressive disorder and post-traumatic stress disorder. The research revealed evidence linking lower synaptic density to network alterations and symptoms of depression.Source: Nature Communications
Connectome-based prediction of cocaine abstinence
Sarah Yip, PhD, MSc, Assistant Professor of Psychiatry, is the first author of a paper published in The American Journal of Psychiatry that tracks the results of a study that used connectome-based predictive modeling to identify neural networks predictive of future abstinence from cocaine.Source: The American Journal of Psychiatry
Mapping metabolism with a Yale-developed imaging technique
Yale researchers have developed a new imaging technique that captures detailed information about metabolism, which plays a role in many diseases. The novel yet simple technique, which harnesses existing technology, could potentially be used to evaluate the effectiveness of drug therapies for cancer and other conditions, the researchers said.
Cerebellar and prefrontal cortical alterations in PTSD: Structural and functional evidence
A Yale Department of Psychiatry and Yale School of Medicine paper published in Chronic Stress shows converging structural and functional evidence for cerebellum abnormalities in posttraumatic stress disorder. Sophie Holmes, PhD, Associate Research Scientist, is the first author.Source: Chronic Stress