Interpretable machine learning for choosing radiation dose-volume constraints on cardio-pulmonary substructures associated with overall survival in NRG oncology RTOG 0617 Journal Article

   

Authors:	Lee, S. H.; Geng, H.; Arnold, J.; Caruana, R.; Fan, Y.; Rosen, M. A.; Apte, A. P.; Deasy, J. O.; Bradley, J. D.; Xiao, Y.
Article Title:	Interpretable machine learning for choosing radiation dose-volume constraints on cardio-pulmonary substructures associated with overall survival in NRG oncology RTOG 0617
Journal Title:	International Journal of Radiation Oncology, Biology, Physics
Volume:	117
Issue:	5
ISSN:	0360-3016
Publisher:	Elsevier Inc.
Date Published:	2023-12-01
Start Page:	1270
End Page:	1286
Language:	English
DOI:	10.1016/j.ijrobp.2023.06.009
PROVIDER:	EBSCOhost
PROVIDER:	cinahl
PUBMED:	37343707
PMCID:	PMC10728350
DOI/URL:	https://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,shib&db=cin20&AN=173518692&authtype=sso&custid=s2915669&site=ehost-live&scope=site&custid=s2915669
Notes:	Accession Number: 173518692 -- Entry Date: In Process -- Revision Date: 20231114 -- Publication Type: Journal Article -- Journal Subset: Biomedical; Peer Reviewed; USA -- NLM UID: 7603616. -- Source: Cinahl

https://synapse.mskcc.org/synapse/works/has_related_data_chk/211823