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machine learning

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    Prediction of Tumor Grade and Nodal Status in Oropharyngeal and Oral Cavity Squamous-cell Carcinoma Using a Radiomic Approach
    VALERIA ROMEO, RENATO CUOCOLO, CARLO RICCIARDI, LORENZO UGGA, SIRIO COCOZZA, FRANCESCO VERDE, ARNALDO STANZIONE, VIRGINIA NAPOLITANO, DANIELA RUSSO, GIOVANNI IMPROTA, ANDREA ELEFANTE, STEFANIA STAIBANO and ARTURO BRUNETTI
    Anticancer Research January 2020, 40 (1) 271-280; DOI: https://doi.org/10.21873/anticanres.13949
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    6-Hydroxythiobinupharidine Inhibits Migration of LM8 Osteosarcoma Cells by Decreasing Expression of LIM Domain Kinase 1
    MASATO YOSHIZAWA, SEIKOU NAKAMURA, YUKI SUGIYAMA, SHIORI TAMAI, YUKIKO ISHIDA, MARI SUEYOSHI, YUKI TODA, SHIGEKUNI HOSOGI, YOSHITAKA YANO and EISHI ASHIHARA
    Anticancer Research December 2019, 39 (12) 6507-6513; DOI: https://doi.org/10.21873/anticanres.13865
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    Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks
    YU JIN CHA, WON IL JANG, MI-SOOK KIM, HYUNG JUN YOO, EUN KYUNG PAIK, HEE KYUNG JEONG and SANG-MIN YOUN
    Anticancer Research September 2018, 38 (9) 5437-5445; DOI: https://doi.org/10.21873/anticanres.12875

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