Автор: Cohen Название: Multiple Sclerosis Therapeutics ISBN: 0521766273 ISBN-13(EAN): 9780521766272 Издательство: Cambridge Academ Рейтинг: Цена: 22952.00 р. 32789.00-30% Наличие на складе: Есть (1 шт.) Описание: This book comprehensively reviews the current state of clinical trial methods in multiple sclerosis, providing investigators, sponsors and specialists with current knowledge of outcome measures and study designs for disease and symptom management of MS. The fourth edition has been extensively revised and features more than 50% new material.
Автор: Donald E. Goodkin; Richard A. Rudick Название: Multiple Sclerosis ISBN: 1852330333 ISBN-13(EAN): 9781852330330 Издательство: Springer Рейтинг: Цена: 13415.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews the therapeutic developments in clinical trial design that have resulted in new treatment options for patients suffering from MS. Important ethical considerations that arise with the new treatments are included, as well as the perspective on the emergence of MS as a treatable disease.
Описание: The next four sections cover specific subfields of neuroimmunology and autoimmune neurology - the clinical and diagnostic features of multiple sclerosis, other autoimmune conditions of the central nervous system, autoimmune conditions of the peripheral nervous system, and systemic autoimmune conditions that affect the nervous system.
Автор: Martinez Ana Название: Emerging Drugs and Targets for Multiple Sclerosis ISBN: 1788014502 ISBN-13(EAN): 9781788014502 Издательство: Royal Society of Chemistry Рейтинг: Цена: 25186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An ideal reference for any student or researcher interested in drug development for neurodegenerative diseases, autoimmune diseases and MS in particular.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Massimo Filippi; Giancarlo Comi Название: New Frontiers of MR-based Techniques in Multiple Sclerosis ISBN: 8847022398 ISBN-13(EAN): 9788847022393 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: House, Patrick Название: Translational Methods for Multiple Sclerosis Research ISBN: 1071612158 ISBN-13(EAN): 9781071612156 Издательство: Springer Рейтинг: Цена: 15855.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume explores the recent advances in the study of translational paths in central inflammation and focuses on ongoing pathophysiological processes and the transition between inflammatory stages and progressive states with neurodegeneration.
Автор: Alan Ebringer Название: Multiple Sclerosis, Mad Cow Disease and Acinetobacter ISBN: 3319377698 ISBN-13(EAN): 9783319377698 Издательство: Springer Рейтинг: Цена: 15957.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores and advances the concept that two neurological diseases, "mad cow disease" and multiple sclerosis, may be linked through exposure to the common microbe Acinetobacter, which is found in human sinuses, on skin and in the soil.
Автор: Picone Название: Multiple Sclerosis Non-Neurologist Pb ISBN: 1975102517 ISBN-13(EAN): 9781975102517 Издательство: Lippincott Williams & Wilkins Рейтинг: Цена: 14336.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed for expert puzzlers, this collection is packed with our trickiest, most mind-boggling Hidden Pictures puzzles - without picture clues! Each book contains more than 100 intricate puzzles paired with only a list of objects to find. And for true puzzle masters, 16 puzzles come with no hints at all. Just right for experienced puzzlers ready to advance to the next level of difficulty.
Автор: Waubant, Emmauelle Название: Multiple Sclerosis, An Issue Of Neurologic Clinics,29-2 ISBN: 1455704695 ISBN-13(EAN): 9781455704699 Издательство: Elsevier Science Рейтинг: Цена: 13705.00 р. Наличие на складе: Нет в наличии.
Описание: Reviews the therapeutic options for multiple sclerosis.
Invited Talks.- Dice overlap measures for objects of unknown number: Application to lesion segmentation.- Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials.- Brain Lesion Image Analysis.- Automated Segmentation of Multiple Sclerosis Lesions using Multi-Dimensional Gated Recurrent Units.- Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation.- MARCEL (inter-Modality Ane Registration with CorELation ratio): An Application for Brain Shift Correction in Ultrasound-Guided Brain Tumor Resection.- Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks.- Overall Survival Time Prediction for High Grade Gliomas based on Sparse Representation Framework.- Traumatic Brain Lesion Quantication based on Mean Diusivity Changes.- Pairwise, Ordinal Outlier Detection of Traumatic Brain Injuries.- Sub-Acute & Chronic Ischemic Stroke Lesion MRI Segmentation.- Brain Tumor Segmentation Using an Adversarial Network.- Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.- Brain Tumor Image Segmentation.- Deep Learning based Multimodal Brain Tumor Diagnosis.- Multimodal Brain Tumor Segmentation using Ensemble of Forest Method.- Pooling-free fully convolutional networks with dense skip connections for semantic segmentation, with application to brain tumor segmentation.- Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks.- 3D Brain Tumor Segmentation through Integrating Multiple 2D FCNNs.- MRI Brain Tumor Segmentation and Patient Survival Prediction using Random Forests and Fully Convolutional Networks.- Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis.- Multimodal Brain Tumor Segmentation Using 3D Convolutional Networks.- A Conditional Adversarial Network for Semantic Segmentation of Brain Tumor.- Dilated Convolutions for Brain Tumor Segmentation in MRI Scans.- Residual Encoder and Convolutional Decoder Neural Network for Glioma Segmentation.- TPCNN: Two-phase Patch-based Convolutional Neural Network for Automatic Brain Tumor Segmentation and Survival Prediction.- Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge.- Multi-modal PixelNet for Brain Tumor Segmentation.- Brain Tumor Segmentation using Dense Fully Convolutional Neural Network.- Brain Tumor Segmentation in MRI Scans using Deeply-Supervised Neural Networks.- Brain Tumor Segmentation and Parsing on MRIs using Multiresolution Neural Networks.- Brain Tumor Segmentation using Deep Fully Convolutional Neural Networks.- Glioblastoma and Survival Prediction.- MRI Augmentation via Elastic Registration for Brain Lesions Segmentation.- Cascaded V-Net using ROI masks for brain tumor segmentation.- Brain Tumor Segmentation using a 3D FCN with Multi-Scale Loss.- Brain tumor segmentation using a multi-path CNN based method.- 3D Deep Neural Network-Based Brain Tumor Segmentation Using Multimodality Magnetic Resonance Sequences.- Automated Brain Tumor Segmentation on Magnetic Resonance Images (MRIs) and Patient Overall Survival Prediction using Support Vector Machines.- Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation.- Tumor segmentation from multimodal MRI using random forest with superpixel and tensor based feature extraction.- Towards Uncertainty-assisted Brain Tumor Segmentation and Survival Prediction.- Ischemic Stroke Lesion Image Segmentation.- WMH Segmentation Challenge: a Texture-based Classication Approach.- White Matter Hyperintensities Segmentation In a Few Seconds Using Fully Convolutional Network and Transfer Learning.
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