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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ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application by Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Sajeeb Saha, Rakib Hossen, Sabbir Ahmed, Mohammad Abu Tareq Rony, Mosammat Farida Akter

“…Additionally, we present a real-time web-based application to operationalize the model, enhancing accessibility for healthcare practitioners and stakeholders.Web app link: https://rajib-research-kedney-diseases-prediction.onrender.com/…”
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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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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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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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Assessing Mobile BRISMA LMS in Flipped Classroom Models to Improve Student Performance: A Structural Equation Modeling Approach by Mahdiyah Mahdiyah, Haris Haris, Basuki Wibawa, Fildzah Rudyah Putri

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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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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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An EWS-LSTM-Based Deep Learning Early Warning System for Industrial Machine Fault Prediction by Fabio Cassano, Anna Maria Crespino, Mariangela Lazoi, Giorgia Specchia, Alessandra Spennato

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A prediction method for anti-cancer drug combinations synergy based on graph attention network by QIN Weiqi;BAO Xin;CHEN Xiao;QIU Jianlong;WANG Donglin

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Prediction of ultimate load capacity of demountable shear stud connectors using machine learning techniques by Ahmed I. Saleh, Nabil S. Mahmoud, Fikry A. Salem, Mohamed Ghannam

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Genotype, Ethnicity, and Drug–Drug Interaction Modeling as Means of Verifying Transporter Biomarker PBPK Model: The Coproporphyrin‐I Story by Yuki Ujihira, Shawn Pei Feng Tan, Daniel Scotcher, Aleksandra Galetin

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