WSU’s AI Arsenal Targets Cancer and Pandemics

In the race against diseases that claim millions of lives annually, Washington State University researchers are deploying artificial intelligence to unlock insights from vast datasets and accelerate breakthroughs in diagnostics and treatment. A flagship web-based informatics tool, spearheaded by Assefaw Gebremedhin, Berry Family Distinguished Associate Professor in the School of Electrical Engineering and Computer Science, promises to transform cancer research by integrating national datasets for real-time analysis.

This platform enables users to probe environmental and behavioral factors, compare molecular profiles and tumor traits across cancer types, and visualize incidence at state and county levels. ‘I am very excited about this work because population-level geospatial analysis of cancer incidence plays a critical role in identifying regional disparities and well-informed public health decision-making,’ Gebremedhin said, as reported by WSU Insider . The tool, now nearing journal submission, builds on prior lab work analyzing molecular drivers in tumors.

Cancer Data Revolution Unfolds

Beyond mapping, the tool addresses inequities tied to socioeconomic status and healthcare access, empowering policymakers with geospatial clustering data. WSU’s efforts align with broader institutional pushes, including the Advancing AI Research Working Group, which fosters cross-disciplinary collaboration amid federal initiatives like the Department of Energy’s Genesis Mission partnering with Pacific Northwest National Laboratory.

In parallel, WSU computer scientists in the Voiland College of Engineering and Architecture have crafted a self-improving AI model for 3D printing, eyeing applications in fabricating artificial organs. This innovation, highlighted in recent university updates, exemplifies how AI optimizes complex manufacturing for medical use.

Viral Threats Meet Machine Precision

Researchers in the College of Veterinary Medicine’s Paul G. Allen School for Global Health have built a machine learning model to pinpoint animal reservoirs harboring viruses transmissible to humans, aiming to avert future pandemics. Complementing this, an interdisciplinary team from the School of Mechanical and Materials Engineering and Department of Veterinary Microbiology and Pathology, led by Jin Liu, employs AI and molecular modeling to dissect thousands of virus-cell interactions.

Liu’s group identified a key herpes virus entry point from myriad interactions. ‘It was just a single interaction from thousands of interactions,’ Liu noted. ‘If we don’t do the simulation and instead did this work by trial and error, it could have taken years to find.’ Their approach accelerates treatment suggestions for viral diseases, as detailed in WSU Insider .

Diagnostics Accelerated by Deep Learning

A deep learning model from WSU identifies pathologies in animal and human tissue images faster and often more accurately than pathologists, slashing analysis time from hours to minutes. Michael Skinner, professor in the School of Biological Sciences, praised it: ‘This AI-based deep learning program was very, very accurate at looking at these tissues. It could revolutionize this type of medicine for both animals and humans.’ The model, published in Scientific Reports and covered by WSU Insider , now collaborates with veterinary teams on wildlife disease diagnostics and holds cancer biopsy promise.

Another tool analyzes hundreds of hair samples in seconds, potentially enabling hair-based health diagnostics, developed by a molecular biosciences graduate student frustrated with manual microscopy. These efforts ramp up WSU’s focus on genomics, pharmaceuticals, and smart health systems.

Ethical Guardrails for AI Medicine

Thomas May, Floyd and Judy Rogers Endowed Professor and medical ethics director at the Elson S. Floyd College of Medicine, cautions on AI’s limits. Privacy risks in datasets, amplified inequities, and overlooked emotional nuances—like a stroke patient’s garden preference over longevity—demand human oversight. ‘A year or two of working in the garden was valued more than five or even 10 years of caring for her grandchildren — to her,’ May illustrated. ‘It’s that sort of emotional element that is unlikely to be reflected in AI data.’

WSU’s initiatives echo regional momentum, such as sociologist Anna Zamora-Kapoor’s NIH AIM-AHEAD fellowship using AI for rural Hispanic lung cancer screening via text interventions, per Elson S. Floyd College of Medicine News . Earlier, Hassan Ghasemzadeh’s team created a machine-learning model predicting cancer patients’ physical test performance from questionnaires, as in WSU Insider (2018).

Broader AI Momentum in the Northwest

WSU’s work integrates with Northwest peers; the University of Washington’s Institute for Protein Design leverages AI for protein engineering against cancer and Alzheimer’s, while Providence and Microsoft collaborate on Prov-GigaPath for pathology. X discussions, including @WSUNews , amplify these advances, noting AI’s role in disparity mapping.

Institutional support, like the AIQ framework for evaluating AI intelligence by Larry Holder and Diane Cook, positions WSU amid national pushes. As AI crunches data exponentially faster, these projects herald a shift in studying and delivering care, blending speed with precision for global health gains.