Indium-111-Leukocyte/Technetium-99m-MDP Bone and Magnetic Resonance Imaging: Difficulty of Diagnosing Osteomyelitis in Patients with Neuropathic Osteoarthropathy von Seabold, James E, Flickinger, Frederick W, Kao, Simon C.S, Gleason, Theodore J, Kahn, Daniel, Nepola, James V, Marsh, J. Lawrence

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Self-mode-locking of a transversely excited N2 laser in the first positive system at 1.048 μm von Gleason, T.J., Willett, C.S., Curnutt, R.M., Kruger, J.S.

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Utilization of Radical Prostatectomy vs. Radiation Therapy for Gleason Grade Group 5 Prostate Cancer before and after USPSTF Grade D Recommendation against Prostate-Specific Antigen Screening in 2012 von Corriher, T.J., Janopaul-Naylor, J., Liu, Y., Dhere, V.R., Sebastian, N., Weiss, A., Hershatter, B., Filson, C.P., Patel, S.A.

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Comparison of the skin tumor initiating activity of 3-methylcholanthrene and 3,11-dimethylcholanthrene in mice von Slaga, T.J., Gleason, G.L., Hardin, L.

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Radical prostatectomy for Gleason 3+3 prostate cancer; who, how and why? Analysis of the British Association of Urological Surgeons complex operations database von John, J.B., Pascoe, J., Fowler, S., Walton, T.J., Johnson, M.I., Aning, J., Challacombe, B.J., McGrath, J.S.

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Gleason grading after neoadjuvant hormonal therapy retains prognostic value for systemic progression following radical prostatectomy von Stewart, S B, Cheville, J C, Sebo, T J, Frank, I, Boorjian, S A, Thompson, R H, Gettman, M T, Tollefson, M K, Umbriet, E C, Psutka, S P, Bergstralh, E J, Rangel, L, Karnes, R J

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Global convergence in the vulnerability of forests to drought von Choat, B, Jansen, S, Brodribb, T.J, Cochard, H, Delzon, S, Bhaskar, R, Bucci, S.J, Feild, T.S, Gleason, S.M, Hacke, U.G, Jacobsen, A.L, Lens, F, Maherali, H, Martínez-Vilalta, J, Mayr, S, Mencuccini, M, Mitchell, P.J, Nardini, A, Pittermann, J, Pratt, R.B, Sperry, J.S, Westoby, M, Wright, I.J, Zanne, A.E

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8.9-Megapixel Video Image Sensor With 14-b Column-Parallel SA-ADC von Matsuo, S., Bales, T.J., Shoda, M., Osawa, S., Kawamura, K., Andersson, A., Munirul Haque, Honda, H., Almond, B., Yaowu Mo, Gleason, J., Chow, T., Takayanagi, I.

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Validation of Ozone Monitoring Instrument nitrogen dioxide columns von Celarier, E. A., Brinksma, E. J., Gleason, J. F., Veefkind, J. P., Cede, A., Herman, J. R., Ionov, D., Goutail, F., Pommereau, J.-P., Lambert, J.-C., van Roozendael, M., Pinardi, G., Wittrock, F., Schönhardt, A., Richter, A., Ibrahim, O. W., Wagner, T., Bojkov, B., Mount, G., Spinei, E., Chen, C. M., Pongetti, T. J., Sander, S. P., Bucsela, E. J., Wenig, M. O., Swart, D. P. J., Volten, H., Kroon, M., Levelt, P. F.

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One Size Does Not Fit All: Evaluating the Need for Separate Unilateral and Bilateral Radiation Therapy Normal Tissue Treatment Planning Goals for Oropharynx Cancer von Wang, L, Flanagan, P, Gleason, R, Murphy, C.T, Churilla, T, Galloway, T.J

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Multi-Stage Classification-Based Deep Learning for Gleason System Grading Using Histopathological Images von Hammouda, Kamal, Khalifa, Fahmi, Alghamdi, Norah Saleh, Darwish, Hanan, El-Baz, Ayman

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Role of Brachytherapy Boost in Clinically Localized Intermediate and High-Risk Prostate Cancer: Lack of Benefit in Patients with Very High-Risk Factors T3b–4 and/or Gleason 9–10 von Yamazaki, Hideya, Suzuki, Gen, Masui, Koji, Aibe, Norihiro, Shimizu, Daisuke, Kimoto, Takuya, Yamada, Kei, Okihara, Koji, Ueda, Takashi, Narukawa, Tsukasa, Shiraishi, Takumi, Fujihara, Atsuko, Yoshida, Ken, Nakamura, Satoaki, Kato, Takashi, Hashimoto, Yasutoshi, Okabe, Haruumi

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Influence of Active Surveillance on Gleason Score Upgrade and Prognosis in Low- and Favorable Intermediate-Risk Prostate Cancer von Hu, Xuanhan, Miao, Jia, Huang, Jiaqing, Qian, Lin, Zhang, Dahong, Wei, Haibin

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Operational exposure of leaf wetness sensors von Sentelhas, Paulo C., Gillespie, Terry J., Gleason, Mark L., Monteiro, José Eduardo B.A., Helland, Sara T.

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Evaluation of a Penman–Monteith approach to provide “reference” and crop canopy leaf wetness duration estimates von Sentelhas, Paulo C., Gillespie, Terry J., Gleason, Mark L., Monteiro, José Eduardo B.M., Pezzopane, José Ricardo M., Pedro, Mário J.

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Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning von Rezaeilouyeh, Hadi, Mahoor, Mohammad

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Classifying Malignancy in Prostate Glandular Structures from Biopsy Scans with Deep Learning von Fogarty, Ryan, Goldgof, Dmitry, Hall, Lawrence, Lopez, Alex, Johnson, Joseph, Gadara, Manoj, Stoyanova, Radka, Punnen, Sanoj, Pollack, Alan, Pow-Sang, Julio, Balagurunathan, Yoganand

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Very-high-risk localized prostate cancer: definition and outcomes von Sundi, D, Wang, V M, Pierorazio, P M, Han, M, Bivalacqua, T J, Ball, M W, Antonarakis, E S, Partin, A W, Schaeffer, E M, Ross, A E

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Outcomes of prostate cancer screening among men using antidiabetic medication von Vettenranta, A., Murtola, T. J., Talala, K., Taari, K., Stenman, U.-H., Tammela, T. L. J., Auvinen, A.

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Automatic diagnosis and grading of Prostate Cancer with weakly supervised learning on whole slide images von Xiang, Jinxi, Wang, Xiyue, Wang, Xinran, Zhang, Jun, Yang, Sen, Yang, Wei, Han, Xiao, Liu, Yueping

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