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In this study, we explore the efficiency of the Monte Carlo Tree Search (MCTS), a prominent decision-making algorithm renowned for its effectiveness in complex decision environments, contingent upon the volume of simulations conducted.
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W. Dai, J. Tao, X. Yan, Z. Feng, and J. Chen, “Addressing unintended bias in toxicity detection: An lstm and attention-based approach,” in 2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA) , 2023, pp. 375–379
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X. Yan, M. Xiao, W. Wang, Y. Li, and F. Zhang, “A self-guided deep learning technique for mri image noise reduction,” Journal of Theory and Practice of Engineering Science , vol. 4, no. 01, pp. 109–117, 2024
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W. Weimin, L. Yufeng, Y. Xu, X. Mingxuan, and G. Min, “Enhancing liver segmentation: A deep learning approach with eas feature extraction and multi-scale fusion,” International Journal of Innovative Research in Computer Science & Technology , vol. 12, no. 1, pp. 26–34, 2024
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Z. Zou, M. Careem, A. Dutta, and N. Thawdar, “Joint spatio-temporal precoding for practical non-stationary wireless channels,” IEEE Transactions on Communications , vol. 71, no. 4, pp. 2396–2409, 2023
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Z. Chen, Q. Cheng, L. Wang, Y. Mo, K. Li, and J. Mo, “Optical coherence tomography for in vivo longitudinal monitoring of artificial dermal scaffold,” Lasers in Surgery and Medicine , vol. 55, no. 3, pp. 316–326, 2023
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Z. Zou and A. Dutta, “Capacity achieving by diagonal permutation for mu-mimo channels,” in GLOBECOM 2023-2023 IEEE Global Communications Conference . IEEE, 2023, pp. 2536–2541
2023
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G. Song, Y. Qian, and Y. Wang, “A deep generative adversarial network (gan)-enabled abnormal pedestrian behavior detection at grade crossings,” in SoutheastCon 2023 . IEEE, 2023, pp. 677–684
2023
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L. Gao, G. Cordova, C. Danielson, and R. Fierro, “Autonomous multi-robot servicing for spacecraft operation extension,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2023, pp. 10 729–10 735
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Y. Li, W. Wang, X. Yan, M. Gao, and M. Xiao, “Research on the application of semantic network in disease diagnosis prompts based on medical corpus,” International Journal of Innovative Research in Computer Science & Technology , vol. 12, no. 2, pp. 1–9, 2024
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J. Tian, A. Xiang, Y. Feng, Q. Yang, and H. Liu, “Enhancing disease prediction with a hybrid cnn-lstm framework in ehrs,” Journal of Theory and Practice of Engineering Science , vol. 4, no. 02, p. 8–14, Feb. 2024. [Online]. Available: https://centuryscipub.com/index.php/jtpes/article/view/489
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H. Zang, S. Li, X. Dong, D. Ma, and B. Dang, “Evaluating the social impact of ai in manufacturing: A methodological framework for ethical production,” Academic Journal of Sociology and Management , vol. 2, no. 1, pp. 21–25, 2024
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X. Wei, D. Ma, J. Ou, G. Song, J. Guo, J. W. Robertson, Y. Wang, Q. Wang, and C. Liu, “Narrowing signal distribution by adamantane derivatization for amino acid identification using an α \alpha -hemolysin nanopore,” Nano Letters , 2024
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