Chintan Parmar

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	All	Since 2016
Citations	7168	6958
h-index	27	27
i10-index	30	29

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Co-authors

Hugo AertsDirector AIM @ Harvard-BWH; DFCI; MGHVerified email at dfci.harvard.edu
Emmanuel Rios VelazquezResearcher @ imec The NetherlandsVerified email at imec-nl.nl
Patrick GrossmannPh.D. Candidate conducting research at Harvard Medical School, Dana-Farber Cancer Institute, BWHVerified email at jimmy.harvard.edu
Philippe LambinProfessor of Precision Medicine, Maastricht UniversityVerified email at maastrichtuniversity.nl
Robert GilliesChair of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer CenterVerified email at moffitt.org
Ralph T.H. LeijenaarPostdoc at Maastricht University, Maastricht, the NetherlandsVerified email at maastrichtuniversity.nl
Benjamin Haibe-KainsScientist (Principal Investigator), Princess Margaret Cancer Centre, University Health NetworkVerified email at uhnresearch.ca
John QuackenbushHarvard T.H. Chan School of Public Health, Channing Division of Network Medicine, and Dana-FarberVerified email at hsph.harvard.edu
Raymond H. MakAssociate Professor of Radiation Oncology, Brigham and Women's Hospital/Dana-Farber Cancer InstituteVerified email at lroc.harvard.edu
Andre DekkerProfessor of Clinical Data Science, MAASTRO Clinic, Maastricht University, GROW, Maastricht UMC+Verified email at maastro.nl
Ahmed HosnyMachine Learning @ Dana Farber Cancer InstituteVerified email at dfci.harvard.edu
Thibaud CorollerResearcher @ NovartisVerified email at novartis.com
Frank HoebersDepartment of Radiation Oncology (MAASTRO), Research Institute GROW, Maastricht UniversityVerified email at maastro.nl
Elizabeth HuynhHarvard Medical SchoolVerified email at bwh.harvard.edu
Andrey FedorovRadiology, Brigham and Women's Hospital, Harvard Medical SchoolVerified email at bwh.harvard.edu
Wouter van ElmptMaastricht University Medical CentreVerified email at maastro.nl
G. Mike MakrigiorgosProfessor of Radiation Oncology, Dana Farber Cancer Institute, Harvard Medical SchoolVerified email at dfci.harvard.edu
Sushmita MitraProfessor, Machine Intelligence Unit, Indian Statistical Institute, KolkataVerified email at isical.ac.in
Manjunath V. JoshiProfessor, Dhirubhai Ambani Institute of Information and Communication TechnologyVerified email at daiict.ac.in
Milind G. PadalkarPostdoc, PAVIS, Istituto Italiano di Tecnologia, Genova, ItalyVerified email at iit.it

Chintan Parmar

Novartis Institutes for Biomedical Research (Current) | Harvard-DFCI-BWH (Previous)

Verified email at dfci.harvard.edu - Homepage

Artificial Intelligence Biomedical Informatics Oncology Data Science Medical Image Analysis


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Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach HJWL Aerts, ER Velazquez, RTH Leijenaar, C Parmar, P Grossmann, ... Nature communications 5 (1), 1-9, 2014	2426	2014
Computational radiomics system to decode the radiographic phenotype JJM Van Griethuysen, A Fedorov, C Parmar, A Hosny, N Aucoin, ... Cancer research 77 (21), e104-e107, 2017	833	2017
Artificial intelligence in radiology A Hosny, C Parmar, J Quackenbush, LH Schwartz, HJWL Aerts Nature Reviews Cancer 18 (8), 500-510, 2018	562	2018
Machine learning methods for quantitative radiomic biomarkers C Parmar, P Grossmann, J Bussink, P Lambin, HJWL Aerts Scientific reports 5, 13087, 2015	505	2015
Robust radiomics feature quantification using semiautomatic volumetric segmentation C Parmar, ER Velazquez, R Leijenaar, M Jermoumi, S Carvalho, RH Mak, ... PloS one 9 (7), e102107, 2014	348	2014
Radiomic feature clusters and prognostic signatures specific for lung and head & neck cancer C Parmar, RTH Leijenaar, P Grossmann, ER Velazquez, J Bussink, ... Scientific reports 5, 11044, 2015	305	2015
Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability RTH Leijenaar, S Carvalho, ER Velazquez, WJC Van Elmpt, C Parmar, ... Acta oncologica 52 (7), 1391-1397, 2013	293	2013
Exploratory study to identify radiomics classifiers for lung cancer histology W Wu, C Parmar, P Grossmann, J Quackenbush, P Lambin, J Bussink, ... Frontiers in oncology 6, 71, 2016	211	2016
Radiomic machine-learning classifiers for prognostic biomarkers of head and neck cancer C Parmar, P Grossmann, D Rietveld, MM Rietbergen, P Lambin, ... Frontiers in oncology 5, 272, 2015	203	2015
Somatic mutations drive distinct imaging phenotypes in lung cancer ER Velazquez, C Parmar, Y Liu, TP Coroller, G Cruz, O Stringfield, Z Ye, ... Cancer research 77 (14), 3922-3930, 2017	163	2017
Volumetric CT-based segmentation of NSCLC using 3D-Slicer ER Velazquez, C Parmar, M Jermoumi, RH Mak, A Van Baardwijk, ... Scientific reports 3, 3529, 2013	145	2013
Defining the biological basis of radiomic phenotypes in lung cancer P Grossmann, O Stringfield, N El-Hachem, MM Bui, ER Velazquez, ... Elife 6, e23421, 2017	143	2017
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study A Hosny, C Parmar, TP Coroller, P Grossmann, R Zeleznik, A Kumar, ... PLoS medicine 15 (11), e1002711, 2018	122	2018
Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR HJWLA Stefano Trebeschi, Joost JM van Griethuysen, Doenja MJ Lambregts, Max ... Scientific Reports 7 (1), 5301, 2017	117*	2017
Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers S Trebeschi, SG Drago, NJ Birkbak, I Kurilova, AM Cǎlin, A Delli Pizzi, ... Annals of Oncology 30 (6), 998-1004, 2019	95	2019
Associations between somatic mutations and metabolic imaging phenotypes in non–small cell lung cancer SSF Yip, J Kim, TP Coroller, C Parmar, ER Velazquez, E Huynh, RH Mak, ... Journal of Nuclear Medicine 58 (4), 569-576, 2017	95	2017
Deep learning predicts lung cancer treatment response from serial medical imaging Y Xu, A Hosny, R Zeleznik, C Parmar, T Coroller, I Franco, RH Mak, ... Clinical Cancer Research 25 (11), 3266-3275, 2019	84	2019
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014; 5: 4006 HJ Aerts, ER Velazquez, RT Leijenaar, C Parmar, P Grossmann, ... Epub 2014/06/04. PubMed PubMedCentral, 2014	60	2014
Associations of radiomic data extracted from static and respiratory-gated CT scans with disease recurrence in lung cancer patients treated with SBRT E Huynh, TP Coroller, V Narayan, V Agrawal, J Romano, I Franco, ... PloS one 12 (1), e0169172, 2017	58	2017
Data analysis strategies in medical imaging C Parmar, JD Barry, A Hosny, J Quackenbush, HJWL Aerts Clinical cancer research 24 (15), 3492-3499, 2018	49	2018

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