Neuro

This book covers all relevant techniques of diagnosis as well as interpretations of clinical signs in Clinical Neuro-Ophthalmology.

This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others.

This book presents 57 typical cases of neuro-ophthalmic diseases in the emergency room, which represent notoriously complex and difficult challenges for junior doctors. The physical manifestations of these neurologic disorders include visual loss, transient blurring, diplopia, headache, pupillary abnormality, and even cognition problems. Each case provides a wealth of information, including the case report, comments, diagnosis, management, prognosis and concise notes, as well as photographs and other images. As a case-based clinical reference work on neuro-ophthalmic diseases, the book offers readers essential, concretely applicable information and guidance.

Although neural modeling has a long history, most of the texts available on the subject are quite limited in scope, dealing primarily with the simulation of large-scale biological neural networks applicable to describing brain function.

Part of the Neurosurgical Operative Atlas series, this volume presents contemporary operative procedures in neuro-oncology. It offers an accessible, step-by-step guide to the latest treatments and considerations in neuro-oncology, with extended coverage of every stage of each procedure, from patient selection, to preoperative planning, to operative techniques and post-operative management.