Rolling Bearing Life Prediction Based on Improved Transformer Encoding Layer and Multi-Scale Convolution by Zhuopeng Luo, Zhihai Wang, Xiaoqin Liu, Yingming Yang

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LSTM-based prediction method for shape error of steel truss during incremental launching construction. by Zhe Hu, Hao Chen, Chunguang Dong, Qinhe Li, Ronghui Wang

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Prediction of cccDNA dynamics in hepatitis B patients by a combination of serum surrogate markers. by Kwang Su Kim, Masashi Iwamoto, Kosaku Kitagawa, Hyeongki Park, Sanae Hayashi, Senko Tsukuda, Takeshi Matsui, Masanori Atsukawa, Kentaro Matsuura, Natthaya Chuaypen, Pisit Tangkijvanich, Lena Allweiss, Takara Nishiyama, Naotoshi Nakamura, Yasuhisa Fujita, Eiryo Kawakami, Shinji Nakaoka, Masamichi Muramatsu, Kazuyuki Aihara, Takaji Wakita, Alan S Perelson, Maura Dandri, Koichi Watashi, Shingo Iwami, Yasuhito Tanaka

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Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine by Nana Zhang, Shi Ying, Kun Zhu, Dandan Zhu

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Machine Learning-Based Approach for HIV/AIDS Prediction: Feature Selection and Data Balancing Strategy by Abdul Mizwar A Rahim, Ahmad Ridwan, Bambang Pilu Hartato, Firman Asharudin

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Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda by Sandra Ruth Babirye, Mike Nsubuga, Gerald Mboowa, Charles Batte, Ronald Galiwango, David Patrick Kateete

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MFE-DDI: A multi-view feature encoding framework for drug-drug interaction prediction by Lingfeng Wang, Yinghong Li, Yaozheng Zhou, Liping Guo, Congzhou Chen

“…In this study, we propose the Multi-view Feature Embedding for drug-drug interaction prediction (MFE-DDI), which integrates SMILES information, molecular graph data and atom spatial semantic information to model drugs from multiple perspectives and encapsulate the intricate drug information crucial for predicting DDIs. …”
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Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data by Alireza Farnoush, Zahra Sedighi-Maman, Behnam Rasoolian, Jonathan J. Heath, Banafsheh Fallah

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Steering-Angle Prediction and Controller Design Based on Improved YOLOv5 for Steering-by-Wire System by Cunliang Ye, Yunlong Wang, Yongfu Wang, Yan Liu

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An immune-related signature based on molecular subtypes for predicting the prognosis and immunotherapy efficacy of hepatocellular carcinoma by Xuhui Sun, Wenlong Jia, Huifang Liang, Henghui Cheng

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Deep learning-based InSAR time-series deformation prediction in coal mine areas by Chuanzeng Shu, Zhiguo Meng, Ying Yang, Yongzhi Wang, Shanjun Liu, Xiaoping Zhang, Yuanzhi Zhang

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Development and validation of a nomogram for predicting the risk of mental health problems of factory workers and miners by Qi Liu, Tao Liu, Yaoqin Lu, Huan Yan

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Predicting drug-target interactions using machine learning with improved data balancing and feature engineering by Md. Alamin Talukder, Mohsin Kazi, Ammar Alazab

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Research on Pump Down Treating Pressure Prediction Based on New Particle Swarm Optimization Algorithm by LIU Mingming, SONG Zhiyong, MA Shou, WEI Yuhua, ZHUANG Huanle

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Neural-Network-Based Prediction of Non-Burial Overwintering Material Covering Height for Wine Grapes by Yunlong Ma, Jinyue Yang, Yibo Chen, Ping Wang, Qinming Sun

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Prediction of hub genes in pulpal inflammation and regeneration using autoencoders and a generative AI approach by Pradeep K. Yadalam, Jogikalmat Krithikadatta, Prabhu M. Natarajan, Carlos M. Ardila

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Data-Driven Prediction Methods for Lithium-Ion Battery State of Health Based on Elbow Rule by Liu Zhang, Bo Xing, Yanbing Gao, Lei Yao, Dengfeng Zhao, Jinquan Ding, Yanyan Li

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Machine learning-based ultrasound radiomics for predicting TP53 mutation status in hepatocellular carcinoma by Didi Bu, Shaobo Duan, Shanshan Ren, Yujing Ma, Yuanyuan Liu, Yahong Li, Xiguo Cai, Lianzhong Zhang, Lianzhong Zhang, Lianzhong Zhang

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Distributed Photovoltaic Short-Term Power Prediction Based on Personalized Federated Multi-Task Learning by Wenxiang Luo, Yang Shen, Zewen Li, Fangming Deng

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Data-driven approaches for predicting Tommy John Surgery risk in major league baseball pitchers by Bosuk Kang, Minsu Park, Angel P. del Pobil, Eunil Park

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