AI-assisted clinical decision making (CDM) for dose prescription in radiosurgery of brain metastases using three-path three-dimensional CNN
Tài liệu tham khảo
Fraass, 1998, American association of physicists in medicine radiation therapy committee task group 53: quality assurance for clinical radiotherapy treatment planning, Med Phys, 25, 1773, 10.1118/1.598373
Huynh, 2020, Artificial intelligence in radiation oncology, Nat Rev Clin Oncol, 17, 771, 10.1038/s41571-020-0417-8
Ezzell, 2003, Guidance document on delivery, treatment planning, and clinical implementation of IMRT: report of the IMRT Subcommittee of the AAPM radiation therapy committee, Med Phys, 30, 2089, 10.1118/1.1591194
Barton, 2006, Role of radiotherapy in cancer control in low-income and middle-income countries, Lancet Oncol, 7, 584, 10.1016/S1470-2045(06)70759-8
Zubizarreta, 2015, Need for radiotherapy in low and middle income countries–the silent crisis continues, Clin Oncol, 27, 107, 10.1016/j.clon.2014.10.006
Wang D, Wang L, Zhang Z, Wang D, Zhu H, Gao Y, et al. “Brilliant AI Doctor” in Rural Clinics: Challenges in AI-Powered Clinical Decision Support System Deployment. Proc. 2021 CHI Conf. Hum. Factors Comput. Syst., 2021, p. 1–18.
Kompa, 2021, Second opinion needed: communicating uncertainty in medical machine learning, NPJ Digit Med, 4, 1, 10.1038/s41746-020-00367-3
Hosny, 2019, Artificial intelligence for global health, Science, 366, 955, 10.1126/science.aay5189
Louis, 2016, The 2016 World Health Organization classification of tumors of the central nervous system: a summary, Acta Neuropathol (Berl), 131, 803, 10.1007/s00401-016-1545-1
Frid-Adar, 2018, GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification, Neurocomputing, 321, 321, 10.1016/j.neucom.2018.09.013
Cao, 2021, Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture, Phys Med Biol, 66, 015003, 10.1088/1361-6560/abca53
Vassantachart, 2022, Automatic differentiation of Grade I and II meningiomas on magnetic resonance image using an asymmetric convolutional neural network, Sci Rep, 12, 10.1038/s41598-022-07859-0
Jiang, 2020, A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration, Phys Med Biol, 65, 015011, 10.1088/1361-6560/ab5da0
Mohammadi, 2021, Deep learning-based Auto-segmentation of Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer, Radiother Oncol, 159, 231, 10.1016/j.radonc.2021.03.030
Xu, 2019, Deep learning predicts lung cancer treatment response from serial medical imaging, Clin Cancer Res, 25, 3266, 10.1158/1078-0432.CCR-18-2495
Zhang, 2022, Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis, Phys Med Biol, 67, 085003, 10.1088/1361-6560/ac5f6e
Jiang, 2021, Enhancement of Four-dimensional Cone-beam Computed Tomography (4D-CBCT) using a Dual-encoder Convolutional Neural Network (DeCNN), IEEE Trans Radiat Plasma Med Sci
Jiang, 2021, Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model, Phys Med Biol, 66, 035009, 10.1088/1361-6560/abcde8
Jiang, 2019, Augmentation of CBCT reconstructed from under-sampled projections using deep learning, IEEE Trans Med Imaging, 38, 2705, 10.1109/TMI.2019.2912791
Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. ArXiv Prepr ArXiv14091556 2014.
Ahmad, 2021, Diagn Pathol, 16, 1, 10.1186/s13000-021-01085-4
Jiang, 2017, Artificial intelligence in healthcare: past, present and future, Stroke Vasc Neurol, 2, 230, 10.1136/svn-2017-000101
LeBlanc, 2017, Patient experiences of acute myeloid leukemia: a qualitative study about diagnosis, illness understanding, and treatment decision-making, Psychooncology, 26, 2063, 10.1002/pon.4309
Strickland, 2019, IBM Watson, heal thyself: how IBM overpromised and underdelivered on AI health care, IEEE Spectr, 56, 24, 10.1109/MSPEC.2019.8678513
Lee, 2018, Assessing concordance with Watson for Oncology, a cognitive computing decision support system for colon cancer treatment in Korea, JCO Clin Cancer Inform, 2, 1
Shaw, 2000, Single dose radiosurgical treatment of recurrent previously irradiated primary brain tumors and brain metastases: final report of RTOG protocol 90–05, Int J Radiat Oncol Biol Phys, 47, 291, 10.1016/S0360-3016(99)00507-6
Glorot, 2010, Understanding the difficulty of training deep feedforward neural networks, Proc Thirteen Int Conf Artif Intell Stat, 249
Kingma DP, Ba J. Adam: A method for stochastic optimization. ArXiv Prepr ArXiv14126980 2014.
Fawcett, 2006, An introduction to ROC analysis, Pattern Recognit Lett, 27, 861, 10.1016/j.patrec.2005.10.010
Pedregosa, 2011, Scikit-learn: machine learning in Python, J Mach Learn Res, 12, 2825