Hugo Aerts

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Citazioni	20528	18692
Indice H	59	54
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Emmanuel Rios VelazquezResearcher @ imec The NetherlandsEmail verificata su imec-nl.nl
Chintan ParmarNovartis Institutes for Biomedical Research (Current) | Harvard-DFCI-BWH (Previous)Email verificata su dfci.harvard.edu
Andre DekkerProfessor of Clinical Data Science, MAASTRO Clinic, Maastricht University, GROW, Maastricht UMC+Email verificata su maastro.nl
Raymond H. MakAssociate Professor of Radiation Oncology, Brigham and Women's Hospital/Dana-Farber Cancer InstituteEmail verificata su lroc.harvard.edu
Patrick GrossmannPh.D. Candidate conducting research at Harvard Medical School, Dana-Farber Cancer Institute, BWHEmail verificata su jimmy.harvard.edu
Benjamin Haibe-KainsScientist (Principal Investigator), Princess Margaret Cancer Centre, University Health NetworkEmail verificata su uhnresearch.ca
Robert GilliesChair of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer CenterEmail verificata su moffitt.org
Thibaud CorollerResearcher @ NovartisEmail verificata su novartis.com
John QuackenbushHarvard T.H. Chan School of Public Health, Channing Division of Network Medicine, and Dana-FarberEmail verificata su hsph.harvard.edu
Nicolai Juul BirkbakAssociate professor, Department of Molecular Medicine (MOMA), Aarhus UniversityEmail verificata su clin.au.dk
Udo HoffmannProfessor of Radiology, Harvard University, Massachusetts General HospitalEmail verificata su mgh.harvard.edu
Andrew H. BeckCo-Founder and CEO at PathAIEmail verificata su PathAI.com
Elizabeth HuynhHarvard Medical SchoolEmail verificata su bwh.harvard.edu
Bradly WoutersPrincess Margaret Cancer CentreEmail verificata su uhnresearch.ca
Ronald BoellaardProfessor Clinical Physics of Positron Emission Tomography, VUmc, AmsterdamEmail verificata su vumc.nl
Dmitry GoldgofProfessor of Computer Science and Engineering, University of South Florida, Moffitt Cancer CenterEmail verificata su mail.usf.edu
Matthew B. Schabath, Ph.D.H. Lee Moffitt Cancer Center & Research InstituteEmail verificata su moffitt.org
Anna GoldenbergScientist, SickKids Research Institute; Assistant Professor Department of Computer Science, University of TorontoEmail verificata su utoronto.ca
Ron KikinisB. Leonard Holman Professor of Radiology, Harvard Medical SchoolEmail verificata su bwh.harvard.edu
David GutmanAssistant Professor of Neurology, Psychiatry, Biomedical Informatics, Emory UniversityEmail verificata su emory.edu

Hugo Aerts

Director AIM @ Harvard-BWH; DFCI; MGH

Email verificata su dfci.harvard.edu - Home page

Deep Learning Artificial Intelligence Bioinformatics Radiomics Radiogenomics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	2420	2014
Radiomics: extracting more information from medical images using advanced feature analysis P Lambin, E Rios-Velazquez, R Leijenaar, S Carvalho, ... European journal of cancer 48 (4), 441-446, 2012	1967	2012
Radiomics: the process and the challenges V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich, MB Schabath, K Forster, ... Magnetic resonance imaging 30 (9), 1234-1248, 2012	1094	2012
Tracking the evolution of non–small-cell lung cancer M Jamal-Hanjani, GA Wilson, N McGranahan, NJ Birkbak, TBK Watkins, ... New England Journal of Medicine 376 (22), 2109-2121, 2017	1073	2017
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	827	2017
Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution C Abbosh, NJ Birkbak, GA Wilson, M Jamal-Hanjani, T Constantin, ... Nature 545 (7655), 446-451, 2017	702	2017
Artificial intelligence in radiology A Hosny, C Parmar, J Quackenbush, LH Schwartz, HJWL Aerts Nature Reviews Cancer 18 (8), 500-510, 2018	555	2018
Machine learning methods for quantitative radiomic biomarkers C Parmar, P Grossmann, J Bussink, P Lambin, HJWL Aerts Scientific reports 5, 13087, 2015	503	2015
Imaging biomarker roadmap for cancer studies JPB O'Connor, EO Aboagye, JE Adams, HJWL Aerts, SF Barrington, ... Nature reviews Clinical oncology 14 (3), 169-186, 2017	475	2017
CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma TP Coroller, P Grossmann, Y Hou, ER Velazquez, RTH Leijenaar, ... Radiotherapy and Oncology 114 (3), 345-350, 2015	461	2015
Applications and limitations of radiomics SSF Yip, HJWL Aerts Physics in Medicine & Biology 61 (13), R150, 2016	435	2016
Inconsistency in large pharmacogenomic studies B Haibe-Kains, N El-Hachem, NJ Birkbak, AC Jin, AH Beck, HJWL Aerts, ... Nature 504 (7480), 389-393, 2013	406	2013
Allele-specific HLA loss and immune escape in lung cancer evolution N McGranahan, R Rosenthal, CT Hiley, AJ Rowan, TBK Watkins, ... Cell 171 (6), 1259-1271. e11, 2017	405	2017
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping A Zwanenburg, M Vallières, MA Abdalah, HJWL Aerts, V Andrearczyk, ... Radiology 295 (2), 328-338, 2020	385	2020
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	347	2014
Predicting outcomes in radiation oncology—multifactorial decision support systems P Lambin, RGPM Van Stiphout, MHW Starmans, E Rios-Velazquez, ... Nature reviews Clinical oncology 10 (1), 27-40, 2013	323	2013
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	306	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
The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis RTH Leijenaar, G Nalbantov, S Carvalho, WJ Van Elmpt, EGC Troost, ... Scientific reports 5, 11075, 2015	261	2015
The potential of radiomic-based phenotyping in precision medicine: a review HJWL Aerts JAMA oncology 2 (12), 1636-1642, 2016	234	2016

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