Role of telomere maintenance genes as a predictive biomarker for colorectal cancer immunotherapy response and prognosis by Zhikai Wang, Chunyan Zhao, Yifen Huang, Chong Li

“…Immune cell infiltration was evaluated through ssGSEA, TIMER, and MCP-Counter tools, and chemotherapy responses were predicted using the pRRophetic package. …”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

“…Inputs such as terrain features, soil characteristics, vegetation indices, and rainfall patterns were utilized to train and evaluate the models. The DEC, DRT, and MLANT models were compared to traditional susceptibility models to assess improvements in prediction accuracy and adaptability.Results and DiscussionsThe results demonstrated significant improvements in prediction accuracy when using the proposed models. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Our method employs Long Short-Term Memory networks and Transformer architectures to model complex temporal dependencies in I/O traces, generating predictive access probability distributions for data blocks. …”
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Model Predictive Control-Based Energy Management System for Cooperative Optimization of Grid-Connected Microgrids by Sungmin Lim, Jaekyu Lee, Sangyub Lee

“…First, the performance of the algorithm was evaluated under various weather conditions. Second, its robustness against prediction errors was tested by comparing scenarios with and without disturbance prediction. …”
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Predictive fatigue life modelling for aluminum alloys winder high temperature and shot peening interact by Allawi H. Alwin, Hatem Ksibi

“…This model was compared with Miner’s rule to assess its predictive accuracy. The results show that the new model provides more accurate predictions of fatigue life than Miner’s rule, thereby improving the reliability and safety of components in high-temperature applications. …”
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Application of Thermodynamic Models to Predict the Solubility of Biologically Active Substances by K. S. Stepanov, G. N. Turmanidze, V. V. Sorokin, A. D. Sakharov

“…Theoretical determination of the dissolving power of various solvents with respect to hesperidin and glycyrrhizic acid.Materials and methods. The PMUNIFAC and NRTL-SAC thermodynamic models were used to predict solubility. …”
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Predictive modeling of rapid glaucoma progression based on systemic data from electronic medical records by Richul Oh, Hyunjoong Kim, Tae-Woo Kim, Eun Ji Lee

“…Systemic data obtained within 6 months from the time of glaucoma diagnosis were extracted from the EMRs and incorporated into a model to predict the rate of progressive RNFL thinning. The predictive model was trained and tested using a random forest (RF) method and interpreted using Shapley additive explanation plots (SHAP). …”
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Prediction of the Immune Phenotypes of Bladder Cancer Patients for Precision Oncology by Hyuna Cho, Feng Tong, Sungyong You, Sungyoung Jung, Won Hwa Kim, Jayoung Kim

“…Upon further validation in independent cohorts, this gene signature could be developed into a predictive test that can support clinical evaluation and patient care.…”
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Social prediction errors in assisting strangers: the role of outcomes and contexts by Yan Li, Zhiwei Liu

“…IntroductionHelping behavior is a fundamental aspect of social interaction, yet little is known about how accurately helpers can predict the emotional responses of help-seekers, particularly when interacting with strangers.MethodsThis study investigated social prediction errors in helping behavior between strangers and examined how outcomes and contexts influence these errors. …”
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Predicting Voluntary Auditor Change Using the Water Cycle Algorithm by Erfan Safdel, Hoda Eskandar, Hassan Yazdifar

“…Then, Excel and Matlab software were used for implementing methods and predicting auditor change. Thirteen financial and non-financial variables that were extracted from the literature were used to predict auditor change in this research. …”
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Peritoneal Laser Doppler Flowmetry in Predicting and Diagnosing Tertiary Peritonitis by D. S. Parshin, M. A. Topchiyev

“…A total of 768 scans were performed. Evaluation was carried out using the APACHE II scales , abdominal index and SOFA scale. …”
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ClusterEmbed: Efficient Protein Structure Prediction with Clustering and Embeddings by Mu Bowei

“…Protein structure prediction has been revolutionized by methods like AlphaFold2, which rely on large-scale multiple sequence alignments (MSAs) to achieve near-experimental accuracy. …”
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IL-36-related genes predict prognosis of gastric cancer by Ying Zhang, Yanbo Liu, Xin Guan, Meng Qu, Dianxiu Wu, Ning Liu, Zhengkun Lin, Yuqi Liu, Han Wang, Lijuan Yang

“…Hence, this study explored the potential role of IL-36 related genes (IL-36RGs) in GC and built a prognostic risk assessment model for GC based on IL-36RGs, which can help evaluate treatment and prognosis.MethodsFirst, relevant datasets were downloaded from public databases. …”
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Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model by Huan Xu

“…Students’ performance is an important factor for the evaluation of teaching quality in colleges. The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). …”
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Investigating of Machine Learning Based Algorithms for Liver Cirrhosis Prediction by Young Choi, Eunsung Oh

“…The novelty lies in the extensive experimentation and performance evaluations conducted, which reveal substantial improvements in prediction accuracy rates compared to existing methods. …”
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Sea State Parameter Prediction Based on Residual Cross-Attention by Lei Sun, Jun Wang, Zi-Hao Li, Zi-Lu Jiao, Yu-Xiang Ma

“…The combination of onboard estimation and data-driven methods is widely applied for sea state parameter prediction. …”
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Application of machine learning in predicting adolescent Internet behavioral addiction by Yao Gan, Li Kuang, Xiao-Ming Xu, Ming Ai, Jing-Lan He, Wo Wang, Su Hong, Jian mei Chen, Jun Cao, Qi Zhang

“…ObjectiveTo explore the risk factors affecting adolescents’ Internet addiction behavior and build a prediction model for adolescents’ Internet addiction behavior based on machine learning algorithms.MethodsA total of 4461 high school students in Chongqing were selected using stratified cluster sampling, and questionnaires were administered. …”
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Utilizing the Attention Mechanism for Accuracy Prediction in Quantized Neural Networks by Lu Wei, Zhong Ma, Chaojie Yang, Qin Yao, Wei Zheng

“…This method predicts a quantized model’s accuracy using a single representative image from the test set. …”
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Computational prediction of protein interactions in single cells by proximity sequencing. by Junjie Xia, Hoang Van Phan, Luke Vistain, Mengjie Chen, Aly A Khan, Savaş Tay

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Machine learning modeling for predicting adherence to physical activity guideline by Ju-Pil Choe, Seungbak Lee, Minsoo Kang

“…The decision tree using all variables emerged as the most effective method in the prediction for PA guidelines (accuracy = 0.705, F1 score = 0.819, and AUC = 0.542). …”
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