MARC details
000 -LEADER |
fixed length control field |
04124nam a22006255i 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
TR-AnTOB |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20231109085904.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220202s2022 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783030830472 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-3-030-83047-2 |
Source of number or code |
doi |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
TR-AnTOB |
Language of cataloging |
eng |
Description conventions |
rda |
Transcribing agency |
TR-AnTOB |
060 ## - NATIONAL LIBRARY OF MEDICINE CALL NUMBER |
Classification number |
WN 250 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
MMPH |
Source |
bicssc |
|
Subject category code |
MJCL |
Source |
bicssc |
|
Subject category code |
SCI058000 |
Source |
bisacsh |
|
Subject category code |
MKSH |
Source |
thema |
|
Subject category code |
MJCL |
Source |
thema |
096 ## - LOCALLY ASSIGNED NLM-TYPE CALL NUMBER (OCLC) |
Classification number |
WN250EBK |
041 ## - LANGUAGE CODE |
Language code of text/sound track or separate title |
İngilizce |
245 10 - TITLE STATEMENT |
Title |
Machine and Deep Learning in Oncology, Medical Physics and Radiology |
Medium |
[electronic resource] / |
Statement of responsibility, etc. |
edited by Issam El Naqa, Martin J. Murphy. |
250 ## - EDITION STATEMENT |
Edition statement |
2nd ed. 2022. |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Cham : |
Name of producer, publisher, distributor, manufacturer |
Springer International Publishing : |
-- |
Imprint: Springer, |
Date of production, publication, distribution, manufacture, or copyright notice |
2022. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
1 online resource |
336 ## - CONTENT TYPE |
Content type term |
text |
Content type code |
txt |
Source |
rdacontent |
337 ## - MEDIA TYPE |
Media type term |
computer |
Media type code |
c |
Source |
rdamedia |
338 ## - CARRIER TYPE |
Carrier type term |
online resource |
Carrier type code |
cr |
Source |
rdacarrier |
347 ## - DIGITAL FILE CHARACTERISTICS |
File type |
text file |
Encoding format |
PDF |
Source |
rda |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Part I. Introduction -- 1. What are Machine and Deep Learning? -- 2. Computational Learning Basics -- 3. Overview of Conventional Machine Learning Methods -- 4. Overview of Deep Machine Learning Methods -- 5. Quantum Computing for Machine Learning -- 6. Performance Evaluation -- 7. Software Tools for Machine and Deep learning -- 8. Data sharing, protection and bioethics -- Part II. Machine Learning for Medical Image Analysis -- 9. Detection of Cancer Lesions from Imaging -- 10. Diagnosis of Malignant and Benign Tumours -- 11. Auto-contouring for image-guidance and treatment planning -- Part III. Machine Learning for Treatment planning & Delivery -- 12. Quality Assurance and error prediction -- 13. Knowledge-based treatment planning -- 14. Intelligent respiratory motion management -- Part IV. Machine Learning for Outcomes Modeling and Decision Support -- 15. Prediction of oncology treatment outcomes -- 16. Radiomics and radiogenomics -- 17. Modelling of Radiotherapy Response (TCP/NTCP) -- 18. Smart adaptive treatment strategies -- 19. Machine learning in clinical trials. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities. . |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Medical radiology. |
|
Topical term or geographic name entry element |
Oncology. |
|
Topical term or geographic name entry element |
Machine learning. |
|
Topical term or geographic name entry element |
Medical physics. |
|
Topical term or geographic name entry element |
Radiology. |
|
Topical term or geographic name entry element |
Biophysics. |
|
Topical term or geographic name entry element |
Radiation Oncology. |
|
Topical term or geographic name entry element |
Machine Learning. |
|
Topical term or geographic name entry element |
Oncology. |
|
Topical term or geographic name entry element |
Medical Physics. |
|
Topical term or geographic name entry element |
Radiology. |
|
Topical term or geographic name entry element |
Biophysics. |
653 #0 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Radiotherapy |
|
Uncontrolled term |
Artificial Intelligence |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
El Naqa, Issam. |
Relator term |
editor. |
Relator code |
edt |
-- |
http://id.loc.gov/vocabulary/relators/edt |
|
Personal name |
Murphy, Martin J. |
Relator term |
editor. |
Relator code |
edt |
-- |
http://id.loc.gov/vocabulary/relators/edt |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="https://doi.org/10.1007/978-3-030-83047-2">https://doi.org/10.1007/978-3-030-83047-2</a> |
Materials specified |
Springer eBooks |
Public note |
Online access link to the resource |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
National Library of Medicine |
Koha item type |
E-Book |