Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables. by Rocco J LaFaro, Suryanarayana Pothula, Keshar Paul Kubal, Mario Emil Inchiosa, Venu M Pothula, Stanley C Yuan, David A Maerz, Lucresia Montes, Stephen M Oleszkiewicz, Albert Yusupov, Richard Perline, Mario Anthony Inchiosa

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Prediction of antipsychotic drug efficacy for schizophrenia treatment based on neural features of the resting-state functional connectome by Song Liu, Meng Wang, Weiyi Han, Anran Chen, Xuzhen Liu, Kang Liu, Xue Li, Yi Chen, Luwen Zhang, Qing Liu, Xiaoge Guo, Xiujuan Wang, Ning Kang, Yong Han, Yuanbo Li, Xi Su, Luxian Lv, Bing Liu, Wenqiang Li, Yongfeng Yang

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Winter Wheat SPAD Prediction Based on Multiple Preprocessing, Sequential Module Fusion, and Feature Mining Methods by Ying Nian, Xiangxiang Su, Hu Yue, Sumera Anwar, Jun Li, Weiqiang Wang, Yali Sheng, Qiang Ma, Jikai Liu, Xinwei Li

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Development and validation of a nomogram for predicting postoperative fever after endoscopic submucosal dissection for colorectal lesions by Jiayu Qiu, Yanhong Xia, Yanxia Zhang, Qingping Ouyang, Liping Wang, Ruiying Ding, Xu Shu, Xiaolin Pan

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Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data by S. Daenens, S. Daenens, S. Daenens, T. Verstraeten, T. Verstraeten, T. Verstraeten, P.-J. Daems, P.-J. Daems, A. Nowé, J. Helsen, J. Helsen, J. Helsen

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Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach by Tomas G Neilan, Judith Mueller, Samuel Peter Heilbroner, Reed Few, Jitesh Chalwa, Francois Charest, Somasekhar Suryadevara, Christine Kratt, Andres Gomez-Caminero, Brian Dreyfus

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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

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Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy by Svetlana Lawrence, Daniel R. Herber, Kamran Eftekhari Shahroudi

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Combined CNN-BiLSTM-Att tourism flow prediction based on VMD-MWPE decomposition reconstruction by Maomao Luo, Danhong Chen, Xinxing Hou, Kang Luo, Tao Wang

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A Method Based on CNN–BiLSTM–Attention for Wind Farm Line Fault Distance Prediction by Ming Zhang, Qingzhong Gao, Baoliang Liu, Chen Zhang, Guangkai Zhou

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LSTM-based framework for predicting point defect percentage in semiconductor materials using simulated XRD patterns by Mehran Motamedi, Reza Shidpour, Mehdi Ezoji

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Prediction of Soil Liquefaction Using a Multi-Algorithm Technique: Stacking Ensemble Techniques and Bayesian Optimization by Long Tsang, Mahdi Akbari, Pouyan Fakharian

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Integration of Single-Cell and Bulk Transcriptome to Reveal an Endothelial Transition Signature Predicting Bladder Cancer Prognosis by Jinyu Yang, Wangxi Wu, Xiaoli Tang

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Enhancing heart disease prediction with stacked ensemble and MCDM-based ranking: an optimized RST-ML approach by T. Ashika, G. Hannah Grace

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Prediction of petrophysical properties through comparative post-stack inversion techniques using advance Neural Networking by Pal Washa Shahzad Rathore, Matloob Hussain, Muhammad Bilal Malik, Sher Afgan

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NetMHCphosPan - Pan-specific prediction of MHC class I antigen presentation of phosphorylated ligands by Carina Thusgaard Refsgaard, Carolina Barra, Xu Peng, Nicola Ternette, Morten Nielsen

“…The improved performance, driven by the extended length and allelic coverage, of NetMHCphosPan over current state-of-the-art methods, was further validated on a large benchmark data set independent from the model development.In conclusion, we have confirmed the high power of NNAlign_MA for motif deconvolution of complex immuno-peptidomics data and have developed a novel method for prediction of MHC presented phosphopeptides with improved predictive power and a broader peptide length and MHC coverage compared to current state-of-the-art methods. …”
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Credit Risk Prediction Using Machine Learning and Deep Learning: A Study on Credit Card Customers by Victor Chang, Sharuga Sivakulasingam, Hai Wang, Siu Tung Wong, Meghana Ashok Ganatra, Jiabin Luo

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SAGEFusionNet: An Auxiliary Supervised Graph Neural Network for Brain Age Prediction as a Neurodegenerative Biomarker by Suraj Kumar, Suman Hazarika, Cota Navin Gupta

“…All models were trained using 5-fold cross-validation to predict brain age and subsequently tested for performance evaluation. …”
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Use of Fourier transform infrared spectroscopy and chemometric analysis to predict the bacilloscopic index in the saliva of leprosy patients by Paulo Cezar de Moraes, Maria Lúcia Scroferneker, Alessandra Koehler, Letícia Maria Eidt, Cristiane Almeida Soares Cattani, Valeriano Antonio Corbellini

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Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification by Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan

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