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Titlebook: HPV and Head and Neck Cancers; Carole Fakhry,Gypsyamber D’Souza Book 2015 The Editor(s) (if applicable) and The Author(s), under exclusive

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https://doi.org/10.1007/978-3-642-82678-8ed neoplasms. Harnessing the immune system to both prevent and treat HPV infections has therefore been an area of significant research effort, innovation and progress over the past decades. Although much of the research performed thus far has been on genital HPV infections, the interaction between o
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Anatomical Sites and Subsites of Head and Neck Cancer,00 newly diagnosed cases annually [1]. These tumours arise from the mucosa of the upper aerodigestive tract, which holds important functional roles for respiration, speech and swallowing. Both surgical and non-surgical treatment modalities achieve a cure for ~50 % of HNSCC patients at 5 years; [2] h
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Frequent Behavioural Questions with an HPV-Positive Malignancy of the Head and Neck,lomavirus (HPV)-positive. This is because HPV-positive malignancy is associated with improved prognosis. However, patients and their partners often wrestle with complex social and behavioural questions. Unfortunately, the answers to many of these questions have not been examined to date. At best, th
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Clinical Management of HPV-Related Oropharyngeal Cancer,demiological evidence has revealed a significant increase in the incidence of oropharyngeal cancer (OPC) in North America and Europe [1–3]. Molecular studies of oropharyngeal tumours have revealed that this increase is due to a rise in the incidence of tumours containing human papillomavirus (HPV),
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The Care of the HPV-Negative Head and Neck Cancer Patient: Presentation, Prognosis, Treatment,ce, Epidemiology, and End Results (SEER) database [1]. From 1988 to 2004, HPV-positive OPC increased by 225 % (95 % CI 208 − 242 %; from 0.8 per 100,000 to 2.6 per 100,000), whereas the incidence of HPV-negative cancers declined by 50 % (95 % CI 47 − 53 %; from 2.0 per 100,000 to 1.0 per 100,000). T
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ifferent vehicles, showing the potential in accuracy and robustness for wear estimation of the Machine Learning based simulation approach. Precise wear estimation of different components of commercial vehicles is crucial to optimize the utilization rate and to guarantee uptime in different applicati
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