Co-Authors
This is a "connection" page, showing publications co-authored by Kathleen Moore and Hong Liu.
Connection Strength
0.478
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Correlation of imaging and plasma based biomarkers to predict response to bevacizumab in epithelial ovarian cancer (EOC). Gynecol Oncol. 2021 05; 161(2):382-388.
Score: 0.181
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Recent advances and clinical applications of deep learning in medical image analysis. Med Image Anal. 2022 07; 79:102444.
Score: 0.049
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Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients. Comput Methods Programs Biomed. 2020 Dec; 197:105759.
Score: 0.044
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Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker. Phys Med Biol. 2018 08 06; 63(15):155020.
Score: 0.038
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Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy. Acad Radiol. 2017 10; 24(10):1233-1239.
Score: 0.035
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A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images. Comput Methods Programs Biomed. 2017 Jun; 144:97-104.
Score: 0.034
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Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome. BMC Med Imaging. 2016 08 31; 16(1):52.
Score: 0.033
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Quantitative measurement of adiposity using CT images to predict the benefit of bevacizumab-based chemotherapy in epithelial ovarian cancer patients. Oncol Lett. 2016 Jul; 12(1):680-686.
Score: 0.033
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Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis. Acta Radiol. 2016 Sep; 57(9):1149-55.
Score: 0.031