| LDR | | 05565cmm u22007938i 4500 |
| 001 | | 000000327764 |
| 003 | | OCoLC |
| 005 | | 20240307140514 |
| 006 | | m d |
| 007 | | cr ||||||||||| |
| 008 | | 230301s2023 flu ob 000 0 eng |
| 010 | |
▼a 2022060987 |
| 015 | |
▼a GBC3B1289
▼2 bnb |
| 016 | 7 |
▼a 021089926
▼2 Uk |
| 019 | |
▼a 1402103057 |
| 020 | |
▼a 9781003094333
▼q (ebook) |
| 020 | |
▼a 1003094333 |
| 020 | |
▼a 9781000903812
▼q (electronic bk. : EPUB) |
| 020 | |
▼a 1000903818
▼q (electronic bk. : EPUB) |
| 020 | |
▼a 9781000903751
▼q (electronic bk. : PDF) |
| 020 | |
▼a 1000903753
▼q (electronic bk. : PDF) |
| 020 | |
▼z 9780367538101
▼q (hardback) |
| 020 | |
▼z 9780367556198
▼q (paperback) |
| 024 | 7 |
▼a 10.1201/9781003094333
▼2 doi |
| 035 | |
▼a 3634209
▼b (N$T) |
| 035 | |
▼a (OCoLC)1377818186
▼z (OCoLC)1402103057 |
| 037 | |
▼a 9781003094333
▼b Taylor & Francis |
| 040 | |
▼a DLC
▼b eng
▼e rda
▼c DLC
▼d YDX
▼d TYFRS
▼d OCLCF
▼d OCLCO
▼d UKMGB
▼d N$T
▼d 248032 |
| 042 | |
▼a pcc |
| 049 | |
▼a MAIN |
| 050 | 00 |
▼a RM849 |
| 072 | 7 |
▼a COM
▼x 037000
▼2 bisacsh |
| 072 | 7 |
▼a MED
▼x 062000
▼2 bisacsh |
| 072 | 7 |
▼a TEC
▼x 059000
▼2 bisacsh |
| 072 | 7 |
▼a PHVD
▼2 bicssc |
| 082 | 00 |
▼a 615.8/42
▼2 23/eng/20230428 |
| 245 | 00 |
▼a Artificial intelligence in radiation oncology and biomedical physics /
▼c edited by Gilmer Valdes and Lei Xing. |
| 250 | |
▼a First edition. |
| 263 | |
▼a 2306 |
| 264 | 1 |
▼a Boca Raton :
▼b CRC Press,
▼c 2023. |
| 300 | |
▼a 1 online resource |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 490 | 0 |
▼a Imaging in medical diagnosis and therapy |
| 504 | |
▼a Includes bibliographical references. |
| 520 | |
▼a "Artificial Intelligence in Radiation Oncology and Biomedical Physics explores how modern machine learning and other AI techniques impact millions of global cancer patients. This pioneering book includes contributions from researchers and clinicians from around the world. Its focus is on the clinical applications of machine learning for medical physics, particularly in radiomics, segmentation, treatment planning, quality assurance, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is envisioned. This book will be an essential companion to radiation oncologists, medical physicists, and medical dosimetrists"--
▼c Provided by publisher. |
| 545 | 0 |
▼a Dr. Gilmer Valdes received his PhD in medical physics from the University of California, Los Angeles, in 2013. He was a postdoctoral fellow with the University of California, San Francisco between 2013-2014 and a medical physics resident from 2014 to 2016 with the University of Pennsylvania. He is currently an associate professor with dual appointments in the Department of Radiation Oncology and the Department of Epidemiology and Biostatistics at the University of California, San Francisco. His main research focus is in the development of algorithms to satisfy special needs that machine learning applications have in medicine. Dr. Lei Xing is the Jacob Haimson & Sarah S. Donaldson Professor and Director of Medical Physics Division of Radiation Oncology Department at Stanford University School of Medicine. He also holds affiliate faculty positions in the Department of Electrical Engineering, Biomedical Informatics, Bio-X and Molecular Imaging Program at Stanford (MIPS). Dr. Xing obtained his PhD in Physics from the Johns Hopkins University and received his medical physics training at the University of Chicago. His research has been focused on artificial intelligence in medicine, medical imaging, treatment planning and dose optimization, medical imaging, imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. He has made unique and significant contributions to each of the above areas. Dr. Xing is an author on more than 400 peer reviewed publications, an inventor/co-inventor on many issued and pending patents, and a co- investigator or principal investigator on numerous NIH, DOD, NSF, RSNA, AAPM, Komen, ACS and corporate grants. He is a fellow of AAPM (American Association of Physicists in Medicine) and AIMBE (American Institute for Medical and Biological Engineering). |
| 588 | |
▼a Description based on print version record and CIP data provided by publisher; resource not viewed. |
| 590 | |
▼a OCLC control number change |
| 650 | 0 |
▼a Radiotherapy
▼x Data processing. |
| 650 | 0 |
▼a Cancer
▼x Radiotherapy
▼x Data processing. |
| 650 | 0 |
▼a Medical physics
▼x Data processing. |
| 650 | 0 |
▼a Artificial intelligence
▼x Medical applications. |
| 650 | 6 |
▼a Radiothe?rapie
▼x Informatique. |
| 650 | 6 |
▼a Cancer
▼x Radiothe?rapie
▼x Informatique. |
| 650 | 6 |
▼a Physique me?dicale
▼x Informatique. |
| 650 | 6 |
▼a Intelligence artificielle en me?decine. |
| 650 | 7 |
▼a COMPUTERS / Machine Theory
▼2 bisacsh |
| 650 | 7 |
▼a MEDICAL / Oncology
▼2 bisacsh |
| 650 | 7 |
▼a Artificial intelligence
▼x Medical applications
▼2 fast |
| 650 | 7 |
▼a Cancer
▼x Radiotherapy
▼x Data processing
▼2 fast |
| 650 | 7 |
▼a Radiotherapy
▼x Data processing
▼2 fast |
| 700 | 1 |
▼a Valdes, Gilmer,
▼e editor. |
| 700 | 1 |
▼a Xing, Lei,
▼e editor. |
| 776 | 08 |
▼i Print version:
▼t Artificial intelligence in radiation oncology and biomedical physics
▼b First edition.
▼d Boca Raton : CRC Press, 2023
▼z 9780367538101
▼w (DLC) 2022060986 |
| 856 | 40 |
▼3 EBSCOhost
▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3634209 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 3634209 |
| 990 | |
▼a 관리자 |
| 994 | |
▼a 92
▼b N$T |