Chintan Parmar

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Hugo AertsDirector AI in Medicine (AIM) @ Harvard-MGB | Professor @ MaastrichtUVerified email at dfci.harvard.edu
Emmanuel Rios VelazquezBusiness Development Manager - Precision Health & Nutrition @imec - OnePlanet Research CenterVerified email at imec.nl
Philippe LambinProfessor of Precision Medicine, Maastricht UniversityVerified email at maastrichtuniversity.nl
Patrick GrossmannPh.D. Candidate conducting research at Harvard Medical School, Dana-Farber Cancer Institute, BWHVerified email at jimmy.harvard.edu
Robert GilliesChair of Cancer Physiology, H. Lee Moffitt Cancer CenterVerified email at moffitt.org
John QuackenbushHarvard T.H. Chan School of Public Health, Channing Division of Network Medicine, and Dana-FarberVerified email at hsph.harvard.edu
Benjamin Haibe-KainsScientist (Principal Investigator), Princess Margaret Cancer Centre, University Health NetworkVerified email at uhnresearch.ca
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
Andrey FedorovRadiology, Brigham and Women's Hospital, Harvard Medical SchoolVerified email at bwh.harvard.edu
Elizabeth HuynhLondon Regional Cancer ProgramVerified email at lhsc.on.ca
Stephen SF Yip, PhDJanssenVerified email at its.jnj.com
Wouter van ElmptMaastricht University Medical CentreVerified email at maastro.nl
Sushmita MitraProfessor, Machine Intelligence Unit, Indian Statistical Institute, KolkataVerified email at isical.ac.in
G. Mike MakrigiorgosProfessor of Radiation Oncology, Dana Farber Cancer Institute, Harvard Medical SchoolVerified email at dfci.harvard.edu
Manjunath V. JoshiProfessor, Dhirubhai Ambani Institute of Information and Communication TechnologyVerified email at daiict.ac.in
Milind Gajanan PadalkarPostdoc, PAVIS, Istituto Italiano di Tecnologia, Genova, ItalyVerified email at iit.it

Chintan Parmar

PathAI (Current) | [Novartis, Harvard-DFCI-BWH, ISI-Kolkata] (Previous)

Verified email at dfci.harvard.edu - Homepage

Artificial Intelligence Biomedical Informatics Oncology Data Science Computational Imaging


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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), 4006, 2014	4134	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	3193	2017
Artificial intelligence in radiology A Hosny, C Parmar, J Quackenbush, LH Schwartz, HJWL Aerts Nature Reviews Cancer 18 (8), 500-510, 2018	1918	2018
Machine learning methods for quantitative radiomic biomarkers C Parmar, P Grossmann, J Bussink, P Lambin, HJWL Aerts Scientific reports 5 (1), 13087, 2015	881	2015
Robust radiomics feature quantification using semiautomatic volumetric segmentation C Parmar, E Rios Velazquez, R Leijenaar, M Jermoumi, S Carvalho, ... PloS one 9 (7), e102107, 2014	564	2014
Radiomic feature clusters and prognostic signatures specific for lung and head & neck cancer C Parmar, RTH Leijenaar, P Grossmann, E Rios Velazquez, J Bussink, ... Scientific reports 5 (1), 1-10, 2015	453	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	430	2013
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	387	2018
Deep learning predicts lung cancer treatment response from serial medical imaginglongitudinal deep learning to track treatment response Y Xu, A Hosny, R Zeleznik, C Parmar, T Coroller, I Franco, RH Mak, ... Clinical Cancer Research 25 (11), 3266-3275, 2019	364	2019
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	354	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	351	2015
Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers S Trebeschi, SG Drago, NJ Birkbak, I Kurilova, AM Cǎlin, AD Pizzi, ... Annals of Oncology 30 (6), 998-1004, 2019	338	2019
Somatic Mutations Drive Distinct Imaging Phenotypes in Lung CancerSomatic Mutations and Radiomic Phenotypes E Rios Velazquez, C Parmar, Y Liu, TP Coroller, G Cruz, O Stringfield, ... Cancer research 77 (14), 3922-3930, 2017	303	2017
Defining the biological basis of radiomic phenotypes in lung cancer P Grossmann, O Stringfield, N El-Hachem, MM Bui, E Rios Velazquez, ... Elife 6, e23421, 2017	275	2017
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	225	2017
Volumetric CT-based segmentation of NSCLC using 3D-Slicer ER Velazquez, C Parmar, M Jermoumi, RH Mak, A van Baardwijk, ... Scientific reports 3 (1), 3529, 2013	210	2013
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	147	2017
Data from NSCLC-radiomics H Aerts, ER Velazquez, RT Leijenaar, C Parmar, P Grossmann, ... The cancer imaging archive, 2015	138	2015
Data Analysis Strategies in Medical ImagingData Science Designs in Medical Imaging C Parmar, JD Barry, A Hosny, J Quackenbush, HJWL Aerts Clinical cancer research 24 (15), 3492-3499, 2018	128	2018
Radiographic prediction of meningioma grade by semantic and radiomic features TP Coroller, WL Bi, E Huynh, M Abedalthagafi, AA Aizer, NF Greenwald, ... PloS one 12 (11), e0187908, 2017	111	2017

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