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Generating reward functions using IRL towards individualized cancer screening.

, , , и . AIH@IJCAI, том 2142 из CEUR Workshop Proceedings, стр. 109-120. CEUR-WS.org, (2018)

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Generating Reward Functions Using IRL Towards Individualized Cancer Screening., , , и . AIH@IJCAI (Revised Selected Papers), том 11326 из Lecture Notes in Computer Science, стр. 213-227. Springer, (2018)Virtual Screening for SHP-2 Specific Inhibitors Using Grid Computing., , , , и . eScience, стр. 555-562. IEEE Computer Society, (2008)An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification., , , , и . Expert Syst. Appl., (2019)Explainable Hierarchical Semantic Convolutional Neural Network for Lung Cancer Diagnosis., , , , и . CVPR Workshops, стр. 63-66. Computer Vision Foundation / IEEE, (2019)An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification., , , , и . CoRR, (2018)A Bayesian model for estimating multi-state disease progression., , , , , , и . Comput. Biol. Medicine, (2017)EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography., , , , и . Medical Imaging: Computer-Aided Diagnosis, том 11314 из SPIE Proceedings, SPIE, (2020)A Continuous Markov Model Approach Using Individual Patient Data to Estimate Mean Sojourn Time of Lung Cancer., , , , , и . AMIA, AMIA, (2015)Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network., , , и . Artif. Intell. Medicine, (2016)A data-driven approach for quality assessment of radiologic interpretations., , , , и . JAMIA, 23 (e1): e152-e156 (2016)