Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials
To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system.
Autor*in: |
Li, Nan [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2017 |
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Umfang: |
9 |
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Übergeordnetes Werk: |
Enthalten in: Xiaokeping-induced autophagy protects pancreatic β-cells against apoptosis under high glucose stress - Wu, Yanyang ELSEVIER, 2018, the official journal of the American Society for Therapeutic Radiology and Oncology, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:97 ; year:2017 ; number:1 ; day:1 ; month:01 ; pages:164-172 ; extent:9 |
Links: |
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DOI / URN: |
10.1016/j.ijrobp.2016.10.005 |
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ELV015071669 |
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Highly Efficient Training, Refinement, and Validation of a Knowledge-based Planning Quality-Control System for Radiation Therapy Clinical Trials |
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To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system. |
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To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system. |
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