Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery

10.1016/j.canlet.2021.04.019

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Bibliographic Details
Main Authors:	Poon, Dennis Jun Jie, Tay, Li Min, Ho, Dean, Chua, Melvin Lee Kiang, Chow, Edward Kai-Hua, Yeo, Eugenia Li Ling
Other Authors:	PHARMACOLOGY
Format:	Others
Published:	Elsevier Ireland Ltd 2022
Subjects:	Artificial intelligence Cancer radioresistance Combinatorial therapeutics Drug development Machine learning
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/233844
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-233844
record_format	dspace
spelling	sg-nus-scholar.10635-2338442024-04-04T04:01:16Z Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery Poon, Dennis Jun Jie Tay, Li Min Ho, Dean Chua, Melvin Lee Kiang Chow, Edward Kai-Hua Yeo, Eugenia Li Ling PHARMACOLOGY DEAN'S OFFICE (DUKE-NUS MEDICAL SCHOOL) COLLEGE OF DESIGN AND ENGINEERING CANCER SCIENCE INSTITUTE OF SINGAPORE Artificial intelligence Cancer radioresistance Combinatorial therapeutics Drug development Machine learning 10.1016/j.canlet.2021.04.019 Cancer Letters 511 56-67 2022-10-26T09:19:56Z 2022-10-26T09:19:56Z 2021-07-01 Others Poon, Dennis Jun Jie, Tay, Li Min, Ho, Dean, Chua, Melvin Lee Kiang, Chow, Edward Kai-Hua, Yeo, Eugenia Li Ling (2021-07-01). Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery. Cancer Letters 511 : 56-67. ScholarBank@NUS Repository. https://doi.org/10.1016/j.canlet.2021.04.019 0304-3835 https://scholarbank.nus.edu.sg/handle/10635/233844 Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/ Elsevier Ireland Ltd Scopus OA2021
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Artificial intelligence Cancer radioresistance Combinatorial therapeutics Drug development Machine learning
spellingShingle	Artificial intelligence Cancer radioresistance Combinatorial therapeutics Drug development Machine learning Poon, Dennis Jun Jie Tay, Li Min Ho, Dean Chua, Melvin Lee Kiang Chow, Edward Kai-Hua Yeo, Eugenia Li Ling Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
description	10.1016/j.canlet.2021.04.019
author2	PHARMACOLOGY
author_facet	PHARMACOLOGY Poon, Dennis Jun Jie Tay, Li Min Ho, Dean Chua, Melvin Lee Kiang Chow, Edward Kai-Hua Yeo, Eugenia Li Ling
format	Others
author	Poon, Dennis Jun Jie Tay, Li Min Ho, Dean Chua, Melvin Lee Kiang Chow, Edward Kai-Hua Yeo, Eugenia Li Ling
author_sort	Poon, Dennis Jun Jie
title	Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
title_short	Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
title_full	Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
title_fullStr	Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
title_full_unstemmed	Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery
title_sort	improving the therapeutic ratio of radiotherapy against radioresistant cancers: leveraging on novel artificial intelligence-based approaches for drug combination discovery
publisher	Elsevier Ireland Ltd
publishDate	2022
url	https://scholarbank.nus.edu.sg/handle/10635/233844
_version_	1800915696314482688

Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery

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