| Repeatability and reproducibility of radiomic features: a systematic review A Traverso, L Wee, A Dekker, R Gillies International Journal of Radiation Oncology* Biology* Physics 102 (4), 1143-1158, 2018 | 706 | 2018 |
| Machine learning algorithms for outcome prediction in (chemo) radiotherapy: An empirical comparison of classifiers TM Deist, FJWM Dankers, G Valdes, R Wijsman, IC Hsu, C Oberije, ... Medical physics 45 (7), 3449-3459, 2018 | 293 | 2018 |
| Vulnerabilities of radiomic signature development: the need for safeguards ML Welch, C McIntosh, B Haibe-Kains, MF Milosevic, L Wee, A Dekker, ... Radiotherapy and Oncology 130, 2-9, 2019 | 290 | 2019 |
| Data from NSCLC-radiomics H Aerts, ER Velazquez, RT Leijenaar, C Parmar, P Grossmann, ... The cancer imaging archive, 2015 | 185 | 2015 |
| Prediction modeling methodology FJWM Dankers, A Traverso, L Wee, SMJ van Kuijk Fundamentals of clinical data science, 101-120, 2019 | 106 | 2019 |
| Artificial intelligence‐based clinical decision support in modern medical physics: selection, acceptance, commissioning, and quality assurance G Mahadevaiah, P Rv, I Bermejo, D Jaffray, A Dekker, L Wee Medical physics 47 (5), e228-e235, 2020 | 105 | 2020 |
| Repeatability and reproducibility study of radiomic features on a phantom and human cohort AK Jha, S Mithun, V Jaiswar, UB Sherkhane, NC Purandare, K Prabhash, ... Scientific reports 11 (1), 2055, 2021 | 92 | 2021 |
| Feasibility of MRI‐only treatment planning for proton therapy in brain and prostate cancers: dose calculation accuracy in substitute CT images L Koivula, L Wee, J Korhonen Medical Physics 43 (8Part1), 4634-4642, 2016 | 88 | 2016 |
| Learning from scanners: Bias reduction and feature correction in radiomics I Zhovannik, J Bussink, A Traverso, Z Shi, P Kalendralis, L Wee, A Dekker, ... Clinical and translational radiation oncology 19, 33-38, 2019 | 75 | 2019 |
| The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques A Traverso, J Van Soest, L Wee, A Dekker Medical physics 45 (10), e854-e862, 2018 | 74 | 2018 |
| Giant magnetoelastic response in MnAs VA Chernenko, L Wee, PG McCormick, R Street Journal of applied physics 85 (11), 7833-7837, 1999 | 74 | 1999 |
| Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing A Traverso, M Kazmierski, Z Shi, P Kalendralis, M Welch, HD Nissen, ... Physica Medica 61, 44-51, 2019 | 65 | 2019 |
| Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients A Traverso, M Kazmierski, ML Welch, J Weiss, S Fiset, WD Foltz, ... Radiotherapy and Oncology 143, 88-94, 2020 | 61 | 2020 |
| Distributed radiomics as a signature validation study using the Personal Health Train infrastructure Z Shi, I Zhovannik, A Traverso, FJWM Dankers, TM Deist, P Kalendralis, ... Scientific data 6 (1), 218, 2019 | 59 | 2019 |
| A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features E Pfaehler, I Zhovannik, L Wei, R Boellaard, A Dekker, R Monshouwer, ... Physics and imaging in radiation oncology 20, 69-75, 2021 | 58 | 2021 |
| Machine learning helps identifying volume-confounding effects in radiomics A Traverso, M Kazmierski, I Zhovannik, M Welch, L Wee, D Jaffray, ... Physica Medica 71, 24-30, 2020 | 56 | 2020 |
| Feasibility of MRI-based reference images for image-guided radiotherapy of the pelvis with either cone-beam computed tomography or planar localization images J Korhonen, M Kapanen, JJ Sonke, L Wee, E Salli, J Keyriläinen, ... Acta oncologica 54 (6), 889-895, 2015 | 51 | 2015 |
| Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics ST Kakileti, HJ Madhu, G Manjunath, L Wee, A Dekker, S Sampangi Artificial Intelligence in Medicine 105, 101854, 2020 | 48 | 2020 |
| Rotatable anisotropy and mixed interfaces: Exchange bias in L Wee, RL Stamps, L Malkinski, Z Celinski Physical Review B 69 (13), 134426, 2004 | 48 | 2004 |
| The AIMe registry for artificial intelligence in biomedical research J Matschinske, N Alcaraz, A Benis, M Golebiewski, DG Grimm, L Heumos, ... Nature methods 18 (10), 1128-1131, 2021 | 47 | 2021 |
Andre DekkerProfessor of Clinical Data Science, MAASTRO Clinic, Maastricht University, GROW, Maastricht UMC+在 maastro.nl 的电子邮件经过验证
