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Learning about NYU Tandon School of Engineering’s Collaborative Take on Healthcare


The latest “Faculty-to-Faculty” event, held on December 9, featured Professor of Computer Science and Engineering Guido Gerig and John T. McDevitt, the Chairman of Biomaterials and Biomimetics at NYU and a Professor in the School of Engineering’s Department of Chemical and Biomolecular Engineering. Faculty members from every department gathered to hear the two explain their latest research and learn more about how engineers are working with physicians to revolutionize healthcare.

Professor Guido Gerig

Professor Guido Gerig

Gerig, among the nation’s most highly regarded authorities in the field of medical image analysis, has worked with radiologists, pediatricians, and psychiatrists to devise ways to extract novel quantitative information from scans of the human brain. His work has led to a deeper understanding of how autism can be predicted, how traumatic brain injuries can best be treated, how the normal brain develops, and more. He explained that medical researchers have access to increasingly large amounts of complex data from a wide variety of modalities and that extracting valuable information from it requires increasingly sophisticated computational methods.

Among the striking images Gerig—who now oversees NYU’s Visualization and Data Analysis (VIDA) lab—displayed during his presentation were scans from a patient with Huntington’s disease, a fatal genetic disorder that causes the progressive breakdown of nerve cells in the brain. While doctors can now treat symptoms of the disease only as they occur, they hope to one day develop pre-symptom treatments that actually slow or stop the progression of the disease—and Gerig’s innovative image analysis methods are helping them.

Professor John T. McDevitt

Professor John T. McDevitt

When he took the lectern, McDevitt told his intently engaged audience of fellow professors about his development of a programmable bio-nano-chip system that makes possible a wide range of biomarker-based disease assessments—quickly, cost-efficiently, and with a large degree of diagnostic sensitivity and specificity. Displaying a photo of a device about the size of an average toaster, he explained that it worked with disposable micro-bead-filled cartridges that when inserted into the unit enabled sophisticated lab-based tests for a variety of conditions, including, for example, heart disease and oral cancer.

McDeviit grew up in Silicon Valley, a milieu that later had a marked influence on his work, convincing him, as he said, that clinicians and patients should “leverage the supercomputer that most of us carry around in our pockets now.” (Because his system is Wi-Fi-enabled, information can be sent to a smartphone, and his team has developed an app that provides cardiac patients with personalized risk assessments.) Other chips in the pipeline include those that would test for signs of prostate cancer, ovarian cancer, drugs of abuse, and traumatic brain injury. McDevitt hopes that his powerful chip-based tools will help bridge the gaps that arise as smart device-enabled healthcare (known as mobile health or mHealth) grows increasingly prevalent. “The same progress we’ve made in diagnosing and treating diabetes, we need to make with other diseases,” he asserted.

Few left the event with any doubt that progress was being made—right here at NYU.