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引用“”的文章Artificial intelligence in radiology

标题/作者	年份
Artificial intelligence in cancer imaging: clinical challenges and applications WL Bi, A Hosny, MB Schabath, ML Giger, NJ Birkbak, A Mehrtash, ... CA: a cancer journal for clinicians 69 (2), 127-157	2019
Algorithms at work: The new contested terrain of control KC Kellogg, MA Valentine, A Christin Academy of Management Annals 14 (1), 366-410	2020
Deep learning in medical image registration: a survey G Haskins, U Kruger, P Yan Machine Vision and Applications 31, 1-18	2020
Tobacco use among sexual minorities in the USA, 1987 to May 2007: a systematic review JGL Lee, GK Griffin, CL Melvin Tobacco control 18 (4), 275-282	2009
Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment P Mikalef, M Boura, G Lekakos, J Krogstie British Journal of Management 30 (2), 272-298	2019
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
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
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
Artificial intelligence for mental health and mental illnesses: an overview S Graham, C Depp, EE Lee, C Nebeker, X Tu, HC Kim, DV Jeste Current psychiatry reports 21, 1-18	2019
Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine Z Ahmed, K Mohamed, S Zeeshan, XQ Dong Database 2020, baaa010	2020
Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges S Huang, J Yang, S Fong, Q Zhao Cancer letters 471, 61-71	2020
Artificial intelligence and the future of global health N Schwalbe, B Wahl The Lancet 395 (10236), 1579-1586	2020
Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation L Zhang, X Wang, D Yang, T Sanford, S Harmon, B Turkbey, BJ Wood, ... IEEE transactions on medical imaging 39 (7), 2531-2540	2020
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis UJ Muehlematter, P Daniore, KN Vokinger The Lancet Digital Health 3 (3), e195-e203	2021
Interpretability of machine learning‐based prediction models in healthcare G Stiglic, P Kocbek, N Fijacko, M Zitnik, K Verbert, L Cilar Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (5 …	2020
Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization T Rahman, A Khandakar, MA Kadir, KR Islam, KF Islam, R Mazhar, ... IEEE Access 8, 191586-191601	2020
A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19) MM Islam, F Karray, R Alhajj, J Zeng Ieee Access 9, 30551-30572	2021
AI applications to medical images: From machine learning to deep learning I Castiglioni, L Rundo, M Codari, G Di Leo, C Salvatore, M Interlenghi, ... Physica Medica 83, 9-24	2021
Radiomics with artificial intelligence: a practical guide for beginners B Koçak, EŞ Durmaz, E Ateş, Ö Kılıçkesmez Diagnostic and interventional radiology 25 (6), 485	2019
Tools and techniques for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19 detection SH Safiabadi Tali, JJ LeBlanc, Z Sadiq, OD Oyewunmi, C Camargo, ... Clinical microbiology reviews 34 (3), 10.1128/cmr. 00228-20	2021

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