Class-balanced negative training sets for improving classifier model predictions of enhancer-promoter interactions by Osamu Maruyama, Tsukasa Koga

“…Further advanced methods in generating negative EPIs should further improve prediction accuracy. The source code is available at https://github.com/maruyama-lab-design/CBOEP2 .…”
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Deep Learning Based LSTM Model for Predicting the Number of Passengers for Public Transport Bus Operators by Joko Siswanto, Danny Manongga, Irwan Sembiring, Sutarto Wijono

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Performance Prediction of the Gearbox Elastic Support Structure Based on Multi-Task Learning by Chengshun Zhu, Zhizhou Lu, Jie Qi, Meng Xiang, Shilong Yuan, Hui Zhang

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Interpretable artificial intelligence model for predicting heart failure severity after acute myocardial infarction by Chenglong Guo, Binyu Gao, Xuexue Han, Tianxing Zhang, Tianqi Tao, Jinggang Xia, Honglei Liu

“…This study aimed to develop an interpretable artificial intelligence (AI) model for HF severity prediction using multidimensional clinical data. …”
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Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease by Ying He, Fan Lin, Xin Zheng, Qiaobin Chen, Meng Xiao, Xiaoting Lin, Hongbiao Huang

“…This study presents a region-specific, interpretable ML model for early IVIG resistance prediction in KD. …”
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Improving drug-drug interaction prediction via in-context learning and judging with large language models by He Qi, He Qi, Xiaoqiang Li, Chengcheng Zhang, Tianyi Zhao, Tianyi Zhao

“…To further refine predictions, we employ GPT-4 as a discriminator to assess the relevance of predictions generated by multiple LLMs.ResultsDDI-JUDGE achieves the best performance among all models in both zero-shot and few-shot settings, with an AUC of 0.642/0.788 and AUPR of 0.629/0.801, respectively. …”
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A hierarchical Bayesian model to predict APOE4 genotype and the age of Alzheimer's disease onset. by Francis Hane, Carolyn Augusta, Owen Bai

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XGBoost models based on non imaging features for the prediction of mild cognitive impairment in older adults by Miguel A. Fernández-Blázquez, José M. Ruiz-Sánchez de León, Rubén Sanz-Blasco, Emilio Verche, Marina Ávila-Villanueva, María José Gil-Moreno, Mercedes Montenegro-Peña, Carmen Terrón, Cristina Fernández-García, Jaime Gómez-Ramírez

“…The aim of this study is to develop and validate machine learning (ML) models based on non-imaging features to predict the risk of MCI conversion in cognitively healthy older adults over a three-year period. …”
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Analysis of influencing factors and trend prediction based on quantile regression and GM(1, 1) model by Lianhui Li, Adham Manyara, Jie Liu

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Integrative machine learning model for subtype identification and prognostic prediction in lung squamous cell carcinoma by Guangliang Duan, Qi Huo, Wei Ni, Fei Ding, Yuefang Ye, Tingting Tang, Huiping Dai

“…Subsequently, four survival machine learning models were developed to predict LUSC prognosis. These models were validated in the testing sets and integrated into an online tool to assist in survival prediction. …”
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AlphaBind, a domain-specific model to predict and optimize antibody–antigen binding affinity by Aditya A. Agarwal, James Harrang, David Noble, Kerry L. McGowan, Adrian W. Lange, Emily Engelhart, Miranda C. Lahman, Jeffrey Adamo, Xin Yu, Oliver Serang, Kyle J. Minch, Kimberly Y. Wellman, David A. Younger, Randolph M. Lopez, Ryan O. Emerson

“…Recent advances in deep learning provide opportunities to address this challenge by learning sequence–function relationships to accurately predict fitness landscapes. These models enable efficient in silico prescreening and optimization of antibody candidates. …”
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Multiplexing and massive parallel sequencing of targeted DNA methylation to predict chronological age by Bowen Zhu, Bowen Zhu, Dean Li, Dean Li, Guojing Han, Xue Yao, Hongqin Gu, Tao Liu, Linghua Liu, Jie Dai, Isabella Zhaotong Liu, Yanlin Liang, Jian Zheng, Zheming Sun, He Lin, Nan Liu, Haidong Yu, Meifang Shi, Gaofang Shen, Zhaohui Hu, Lefeng Qu

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Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy. by Xiaohua Zeng, Changzhou Liang, Qian Yang, Fei Wang, Jieping Cai

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Dynamics of Worm Propagation Model in Complex Networks Considering Benign Worm and Link Prediction Approach by Elham Asadi, Soodeh Hosseini

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Prediction of sleep disorders using Novel decision support neutrosophic based machine learning models by Nihar Ranjan Panda, Surapati Paramanik, Prasanta Kumar Raut, Ruchi Bhuyan

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Mathematical prediction model for ground vibrations of nearby territories induced by high dam flood discharge by Wenjiao Zhang, Jijian Lian, Fang Liu, Xing Zhao, Chao Liang

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Predicting Wind Turbine Blade Tip Deformation With Long Short‐Term Memory (LSTM) Models by Shubham Baisthakur, Breiffni Fitzgerald

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Animal-sourced model of human norovirus infection predicted using environmental DNA metabarcoding analysis by Yukuto Sato, Jun Yasuda, Masahiro Sakurai

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Maxent modeling for predicting the potential distribution of Arbutus andrachne L. belonging to climate change in Turkey. by AYSE GUL SARIKAYA, Omer Kamil ORUCU

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An artificial intelligence-based model for prediction of clonal hematopoiesis variants in cell-free DNA samples by Gustavo Arango-Argoty, Marzieh Haghighi, Gerald J. Sun, Elizabeth Y. Choe, Aleksandra Markovets, J. Carl Barrett, Zhongwu Lai, Etai Jacob

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