Reduced temporal and spatial stability of neural activity patterns predict cognitive control deficits in children with ADHD by Zhiyao Gao, Katherine Duberg, Stacie L. Warren, Li Zheng, Stephen P. Hinshaw, Vinod Menon, Weidong Cai

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Predicting graduation grades using Machine Learning: A case study of Can Tho University students by Minh Khiem Nguyen, Van Tu Huynh, Hung Dung Nguyen

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Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3. by Cristina Savin, Peter Dayan, Máté Lengyel

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A Hybrid Particle Swarm Optimization-Tuning Algorithm for the Prediction of Nanoparticle Morphology from Microscopic Images by Abhishek Singh, Thaseem Thajudeen

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Prediction of all-cause mortality in Parkinson’s disease with explainable artificial intelligence using administrative healthcare data by You Hyun Park, Yong Wook Kim, Dae Ryong Kang, Sang Chul Lee, Seo Yeon Yoon

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Implementation Of Triple Exponential Smoothing Method To Predict Palm Oil Production Of PT.Lonsum Web-Based by syafhira ananda galasca, Aninda Muliani Harahap

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Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence by Daniel Wüstner, Henrik Helge Gundestrup, Katja Thaysen

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Random forest-based frame work for multi-distress prediction in CRCP: a feature importance approach by Ali Alnaqbi, Ghazi G. Al-Khateeb, Waleed Zeiada, Muamer Abuzwidah

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EventFormer: a hierarchical neural point process framework for spatio-temporal clustering events prediction by Shanshan Yu, Danhuai Guo, Yanjie Fu, Wei Jin

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Improved and Interpretable Solar Flare Predictions With Spatial and Topological Features of the Polarity Inversion Line Masked Magnetograms by Hu Sun, Ward Manchester IV, Yang Chen

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Predicting vasovagal reactions to needles from video data using 2D-CNN with GRU and LSTM. by Judita Rudokaite, Sharon Ong, Itir Onal Ertugrul, Mart P Janssen, Elisabeth Huis In 't Veld

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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

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Construction of a dynamic nomogram to predict osteoporosis in elderly maintenance hemodialysis patients based on microinflammatory indicators by Zhu Jing-jing, Fu Yu, Zhou Ya-ping

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Construction of a dynamic nomogram to predict osteoporosis in elderly maintenance hemodialysis patients based on microinflammatory indicators by Zhu Jing-jing, Fu Yu, Zhou Ya-ping

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The interaction between genetic predicted gut microbiome abundance and particulate matter on the risk of incident asthma in adults by Hehua Zhang, Yong Feng, Honghao Yang, Yuqian Li, Zheng Ma, Liuxin Li, Liangkai Chen, Yuhong Zhao, Lishen Shan, Yang Xia

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Rack1 and Pon1 as predictive hub genes in WNT-based oral cancer: an interactomic approach by Yadalam Pradeep Kumar, Ramadoss Ramya, Anegundi Raghavendra Vamsi, Arumuganainar Deepavalli, Brahmbhatt Nilam, Mathew Asok, Ardila Carlos M

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Predicting prognosis using stroke-heart indicator: brain natriuretic peptide in patients with aneurysmal subarachnoid hemorrhage by Jionghao Xue, Jionghao Xue, Fa Lin, Fa Lin, Minghao Liu, Minghao Liu, Wenxiong Song, Wenxiong Song, Runting Li, Runting Li, Yu Chen, Yu Chen, Jun Yang, Jun Yang, Heze Han, Heze Han, Yitong Jia, Yitong Jia, Xiaolin Chen, Xiaolin Chen, Rong Wang, Rong Wang, Yuanli Zhao

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Explainable Machine Learning to Predict the Construction Cost of Power Plant Based on Random Forest and Shapley Method by Suha Falih Mahdi Alazawy, Mohammed Ali Ahmed, Saja Hadi Raheem, Hamza Imran, Luís Filipe Almeida Bernardo, Hugo Alexandre Silva Pinto

“…Accurate cost predictions are essential for project feasibility, and this research highlights the strength of ensemble methods in improving prediction accuracy by combining the advantages of multiple models, offering a significant improvement over traditional approaches. …”
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Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach by Mehewish Musheer Sheikh, Mamatha Balachandra, Narendra V. G., Arun G. Maiya

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Predicting Architectural Space Preferences Using EEG-Based Emotion Analysis: A CNN-LSTM Approach by Ju Eun Cho, Se Yeon Kang, Yi Yeon Hong, Han Jong Jun

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