Board on Health Care Services & Health and Medicine Division 
Improving Cancer Diagnosis and Care [EPUB ebook] 
Clinical Application of Computational Methods in Precision Oncology: Proceedings of a Workshop

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A hallmark of high-quality cancer care is the delivery of the right treatment to the right patient at the right time. Precision oncology therapies, which target specific genetic changes in a patient’s cancer, are changing the nature of cancer treatment by allowing clinicians to select therapies that are most likely to benefit individual patients. In current clinical practice, oncologists are increasingly formulating cancer treatment plans using results from complex laboratory and imaging tests that characterize the molecular underpinnings of an individual patient’s cancer. These molecular fingerprints can be quite complex and heterogeneous, even within a single patient. To enable these molecular tumor characterizations to effectively and safely inform cancer care, the cancer community is working to develop and validate multiparameter omics tests and imaging tests as well as software and computational methods for interpretation of the resulting datasets.To examine opportunities to improve cancer diagnosis and care in the new precision oncology era, the National Cancer Policy Forum developed a two-workshop series. The first workshop focused on patient access to expertise and technologies in oncologic imaging and pathology and was held in February 2018. The second workshop, conducted in collaboration with the Board on Mathematical Sciences and Analytics, was held in October 2018 to examine the use of multidimensional data derived from patients with cancer, and the computational methods that analyze these data to inform cancer treatment decisions. This publication summarizes the presentations and discussions from the second workshop.

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Lingua Inglese ● Formato EPUB ● Pagine 92 ● ISBN 9780309490849 ● Editore Emily Zevon & Margie Patlak ● Casa editrice National Academies Press ● Pubblicato 2019 ● Scaricabile 3 volte ● Moneta EUR ● ID 7145772 ● Protezione dalla copia Adobe DRM
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