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Big Data in Radiation Oncology by Jun Deng (English) Hardcover Book

Description: Big Data in Radiation Oncology by Jun Deng, Lei Xing Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. Basic principles are covered early on, and clinical applications become the focus thereafter. A final section introduces emerging models for cancer prevention and detection. Publisher Description Big Data in Radiation Oncology gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. While basic principles and key analytical and processing techniques are introduced in the early chapters, the rest of the book turns to clinical applications, in particular for cancer registries, informatics, radiomics, radiogenomics, patient safety and quality of care, patient-reported outcomes, comparative effectiveness, treatment planning, and clinical decision-making. More features of the book are: Offers the first focused treatment of the role of big data in the clinic and its impact on radiation therapy. Covers applications in cancer registry, radiomics, patient safety, quality of care, treatment planning, decision making, and other key areas. Discusses the fundamental principles and techniques for processing and analysis of big data. Address the use of big data in cancer prevention, detection, prognosis, and management. Provides practical guidance on implementation for clinicians and other stakeholders.Dr. Jun Deng is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an ABR board certified medical physicist at Yale-New Haven Hospital. He has received numerous honors and awards such as Fellow of Institute of Physics in 2004, AAPM Medical Physics Travel Grant in 2008, ASTRO IGRT Symposium Travel Grant in 2009, AAPM-IPEM Medical Physics Travel Grant in 2011, and Fellow of AAPM in 2013. Lei Xing, Ph.D., is the Jacob Haimson Professor of Medical Physics and Director of Medical Physics Division of Radiation Oncology Department at Stanford University. His research has been focused on inverse treatment planning, tomographic image reconstruction, CT, optical and PET imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is on the editorial boards of a number of journals in radiation physics and medical imaging, and is recipient of numerous awards, including the American Cancer Society Research Scholar Award, The Whitaker Foundation Grant Award, and a Max Planck Institute Fellowship. Author Biography Jun Deng, PhD, is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an American Board of Radiology board-certified medical physicist at Yale New Haven Hospital. Dr. Deng obtained his PhD from the University of Virginia in 1998 and finished his postdoctoral fellowship at the Department of Radiation Oncology of Stanford University in 2001. Dr. Deng joined Yale Universitys Department of Therapeutic Radiology as a faculty physicist in 2001. Dr. Deng serves on the editorial boards of numerous peer-reviewed journals and has served on study sections of the NIH, DOD, ASTRO, and RSNA since 2005 and as a scientific reviewer for the European Science Foundation and the Dutch Cancer Society since 2015. Dr. Deng has received numerous honors and awards such as Fellow of Institute of Physics in 2004, AAPM Medical Physics Travel Grant in 2008, ASTRO IGRT Symposium Travel Grant in 2009, AAPM-IPEM Medical Physics Travel Grant in 2011, and Fellow of AAPM in 2013. At Yale, Dr. Dengs research has focused on big data, machine learning, artificial intelligence, and medical imaging for early cancer detection and prevention. In 2013, his group developed CT Gently®, the worlds first iPhone App that can be used to estimate organ doses and associated cancer risks from CT and CBCT scans. Recently, funded by an NIH R01 grant, his group has been developing a personal organ dose archive (PODA) system for personalized tracking of radiation doses in order to improve patient safety in radiation therapy. Lei Xing, PhD, is currently the Jacob Haimson Professor of Medical Physics and Director of the Medical Physics Division of the Radiation Oncology Department of Stanford University. Dr. Xing obtained his PhD in Physics from the Johns Hopkins University in 1992 and received his Medical Physics training at the University of Chicago. He has been a member of the Radiation Oncology faculty at Stanford since 1997. He is also an affiliated faculty member in Stanfords Department of Electrical Engineering, the Biomedical Informatics Program, the Molecular Imaging Program at Stanford, and the Bio-X program. His research has focused on inverse treatment planning, tomographic image reconstruction, CT, optical and PET imaging instrumentations, image-guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is an author on more than 250 peer-reviewed publications, a co-inventor on many issued and pending patents, and a co-investigator or principal investigator on numerous NIH, DOD, NSF, and ACS grants and projects from other funding agencies and corporations. He and his lab members have received numerous awards from ACS, AAPM, ASTRO, WMIC, and RSNA in the past decade. Dr. Xing serves on the editorial boards of a number of journals in radiation physics and medical imaging and is a recipient of numerous awards, including the American Cancer Society Research Scholar Award, The Whitaker Foundation Grant Award, and a Max Planck Institute Fellowship. Details ISBN 1138633437 ISBN-13 9781138633438 Title Big Data in Radiation Oncology Author Jun Deng, Lei Xing Format Hardcover Year 2019 Pages 310 Publisher Taylor & Francis Ltd GE_Item_ID:139836729; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 185.39 USD

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End Time: 2024-12-27T07:10:49.000Z

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Big Data in Radiation Oncology by Jun Deng (English) Hardcover Book

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Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9781138633438

Book Title: Big Data in Radiation Oncology

Number of Pages: 310 Pages

Publication Name: Big Data in Radiation Oncology

Language: English

Publisher: CRC Press LLC

Publication Year: 2019

Subject: Life Sciences / Biophysics, Oncology, Physics / General, Biomedical

Item Height: 0.9 in

Type: Textbook

Item Weight: 26.7 Oz

Author: Lei Xing

Item Length: 10.2 in

Subject Area: Technology & Engineering, Science, Medical

Series: Imaging in Medical Diagnosis and Therapy Ser.

Item Width: 7.2 in

Format: Hardcover

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