Search Results - "Ayandeh, Siamack"

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories by Placido, Davide, Yuan, Bo, Hjaltelin, Jessica X., Zheng, Chunlei, Haue, Amalie D., Chmura, Piotr J., Yuan, Chen, Kim, Jihye, Umeton, Renato, Antell, Gregory, Chowdhury, Alexander, Franz, Alexandra, Brais, Lauren, Andrews, Elizabeth, Marks, Debora S., Regev, Aviv, Ayandeh, Siamack, Brophy, Mary T., Do, Nhan V., Kraft, Peter, Wolpin, Brian M., Rosenthal, Michael H., Fillmore, Nathanael R., Brunak, Søren, Sander, Chris

“…Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we…”
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The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology by Do, Nhan, Grossman, Robert, Feldman, Theodore, Fillmore, Nathanael, Elbers, Danne, Tuck, David, Dhond, Rupali, Selva, Luis, Meng, Frank, Fitzsimons, Michael, Ajjarapu, Samuel, Ayandeh, Siamack, Hall, Robert, Do, Stephanie, Brophy, Mary

“…The Department of Veterans Affairs (VA) has a strong track record providing high-quality, evidence-based care to cancer patients. In order to accelerate…”
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A predictive model for survival in non-small cell lung cancer (NSCLC) based on electronic health record (EHR) and tumor sequencing data at the Department of Veterans Affairs (VA) by Fillmore, Nathanael, Ramos-Cejudo, Jamie, Cheng, David, Tuck, David P., Sheikh, Ayesha Rizwan, Chen, Daniel, Elbers, Danne, Sung, Feng-Chi, Johnson, Brett, Shannon, Colleen, Pierce-Murray, Karen, Gaynor, Kelly, Dedomenico, Corri, Schiller, Sarah, Ajjarapu, Samuel, Hall, Robert, Ayandeh, Siamack, Meng, Frank, Brophy, Mary T., Do, Nhan

“…Abstract only 109 Background: Machine learning tools based on EHR data hold promise to help avoid unnecessary risks associated with lung cancer and its…”
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A framework for benchmarking performance of switch fabrics by Ayandeh, S.

“…A framework for benchmarking performance of switch fabrics is presented. The framework consists of three components: traffic models, metrics that quantify…”
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