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Titlebook: Radiation Therapy in Hematologic Malignancies; An Illustrated Pract Bouthaina Shbib Dabaja,Andrea K. Ng Book 2017 Springer International Pu

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樓主: Gullet
11#
發(fā)表于 2025-3-23 10:40:07 | 只看該作者
Extranodal NK/T-Cell Lymphoma, Nasal Type,on-Hodgkin’s lymphomas (NHL) in these countries (Vose et al. J Clin Oncol 26:4124–4130, 2008; Au et al. Blood 113:3931–3937, 2009; Sun et al. Am J Clin Pathol 138:429–434, 2012; Yang et al. Diagn Pathol 6:77, 2011). This disease can arise within any extranodal organ or tissue, but usually involves t
12#
發(fā)表于 2025-3-23 15:39:39 | 只看該作者
ature for each option. Finally, the treatment delivered is identified and images of the planning technique/modality used are provided. This book will be an invaluable aid to decision making for radiation oncologists and will also be of interest for hematologists.978-3-319-82619-6978-3-319-42615-0
13#
發(fā)表于 2025-3-23 21:15:51 | 只看該作者
Book 2017dentified and images of the planning technique/modality used are provided. This book will be an invaluable aid to decision making for radiation oncologists and will also be of interest for hematologists.
14#
發(fā)表于 2025-3-24 01:09:53 | 只看該作者
Richard Tsang MD, FRCP(C) it at a given point in time. Finally, . means exhibiting goal-directed behavior [407]. There are many architectures domains of influences and technologies that embody agent systems. When implemented as a system, agents are capable of achieving highly sophisticated goals autonomously and if written
15#
發(fā)表于 2025-3-24 05:06:37 | 只看該作者
16#
發(fā)表于 2025-3-24 10:29:00 | 只看該作者
Chelsea Pinnix MD, PhDectivity. To overcome these challenges, we train state-of-the-art object detection and segmentation models on a ragweed dataset. The best performing segmentation models were compressed using shunt connections, fine-tuned with knowledge distillation, and further optimized with Nvidias TensorRT librar
17#
發(fā)表于 2025-3-24 13:22:28 | 只看該作者
18#
發(fā)表于 2025-3-24 16:14:07 | 只看該作者
19#
發(fā)表于 2025-3-24 19:02:34 | 只看該作者
20#
發(fā)表于 2025-3-25 03:01:22 | 只看該作者
Grace L. Smith MD, PhD, MPHectivity. To overcome these challenges, we train state-of-the-art object detection and segmentation models on a ragweed dataset. The best performing segmentation models were compressed using shunt connections, fine-tuned with knowledge distillation, and further optimized with Nvidias TensorRT librar
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