Carol Wu on Muck Rack

Carol Wu

As seen in: Color Research & Application, Nature, Wiley Online Library, The Lancet, Radiological Society of North America, Texas Medical Center, International Journal of Radiation Oncology*Biology*Physics, Journal of the American College of Radiology, Heart, Lung and Circulation

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Carol Wu’s Biography

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Tritrust is one of the biggest exporter of hospitality equipment in China. We aim to deliver the best professional equipment to you with effective service and a can-do attitude for the hotel, restaurant, cafe and catering industries. We want to be a helpful,elastic and trustworthy business partner with you. All our products highlight our ongoing efforts to bring you the best products. The growing team at Tritust looks forward to working with you into the future to meet your specialised needs.

Articles

Machine-learning driven strategies for adapting immunotherapy in metastatic NSCLC - Nature Communications

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By Qasem Al-Tashi, Lingzhi Hong, Carol Wu, Tina Cascone, Xiuning Le, Yasir Y. Elamin, Mehmet Altan, Simon Heeke, Ajay Sheshadri, don gibbons, J. Lee, Cara Haymaker, Justin F. Gainor, John Heymach, Natalie I. Vokes, Jianjun Zhang
| Nature Verified
Abstract Immune checkpoint inhibitors (ICIs), either as monotherapy (ICI-Mono) or combined with chemotherapy (ICI-Chemo), improves survival in advanced non-small cell lung cancer (NSCLC). However, prospective guidance for choosing between these options remains limited, and single-feature biomarkers like PD-L1 prove inadequate.
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SwarmDeepSurv: Swarm Intelligence Advances Deep Survival Network for Prognostic Radiomics Signatures in Four Solid Cancers

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By Qasem Al-Tashi, Maliazurina B. Saad, Ajay Sheshadri, Carol Wu
| Texas Medical Center
Survival models exist to study relationships between biomarkers and treatment effects. Deep learning-powered survival models supersede the classical Cox proportional hazards (CoxPH) model, but substantial performance drops were observed on high-dimensional features because of irrelevant/redundant information. To fill this gap, we proposed SwarmDeepSurv by integrating swarm intelligence algorithms with the deep survival model.
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Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights - Nature Communications

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By Sheeba J. Sujit, Muhammad Aminu, Pingjun Chen, John Boom, James George, Mara B. Antonoff, Lingzhi Hong, Simon Heeke, Xiuning Le, Yasir Y. Elamin, Mehmet Altan, Natalie I. Vokes, Ajay Sheshadri, Jianhua Zhang, Yang Lu, Carol Wu, J. Lee, don gibbons, John Heymach, Jianjun Zhang, Tina Cascone
| Nature Verified
Abstract While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored.
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