A two phase ensembled deep learning approach of prominent gene extraction and disease risk prediction by Prajna Paramita DEBATA, Alakananda TRIPATHY, Pournamasi PARHI, Smruti Rekha DAS

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Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis. by Trinh Huu Khanh Dong, Liane S Canas, Joseph Donovan, Daniel Beasley, Nguyen Thuy Thuong-Thuong, Nguyen Hoan Phu, Nguyen Thi Ha, Sebastien Ourselin, Reza Razavi, Guy E Thwaites, Marc Modat

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GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass by Mansour Sharabiani, Alireza Mahani, Alex Bottle, Yadav Srinivasan, Richard Issitt, Serban Stoica

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Predictive analysis of solubility data with pressure and temperature in assessing nanomedicine preparation via supercritical carbon dioxide by Hashem O. Alsaab, Yusuf S. Althobaiti

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MCF-DTI: Multi-Scale Convolutional Local–Global Feature Fusion for Drug–Target Interaction Prediction by Jihong Wang, Ruijia He, Xiaodan Wang, Hongjian Li, Yulei Lu

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Application of nine point logic control and predictive pid control algorithms in smart grid decision-making by Zhixin Ou

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Water-Depth-Based Prediction Formula for the Blasting Vibration Velocity of Lighthouse Caused by Underwater Drilling Blasting by Wenbin Gu, Zhenxiong Wang, Jianqing Liu, Jinglin Xu, Xin Liu, Tao Cao

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Review of machine learning applications for predicting the quality of biomass briquettes for sustainable and low-carbon energy solutions by Constance Nakato Nakimuli, Fred Kaggwa, Johan De Greef, David Kilama Okot, Julien Blondeau, Simon Kawuma

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Intelligent prediction method for fire temperature fields in underground exhibition spaces of high-intensity urban areas by Yuan Shi, Yang Zhou, Guanhua Qu, Lan Wang, Rong Wang, Zenghui Liu

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Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

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Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

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Optimizing blood glucose predictions in type 1 diabetes patients using a stacking ensemble approach by Vincent B. Liu, Laura Y. Sue, Oscar Madrid Padilla, Yingnian Wu

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Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis by Jonatan M. Panula, Athanasios Gotsopoulos, Jussi Alho, Jaana Suvisaari, Maija Lindgren, Tuula Kieseppä, Tuukka T. Raij

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Prediction of birthweight with early and mid-pregnancy antenatal markers utilising machine learning and explainable artificial intelligence by Manohar Pavanya, Krishnaraj Chadaga, Vennila J, Akhila Vasudeva, Bhamini Krishna Rao, Srikanth Prabhu, Shashikala K Bhat

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Nature or nurture: genetic and environmental predictors of adiposity gain in adultsResearch in context by Laia Peruchet-Noray, Niki Dimou, Reynalda Cordova, Emma Fontvieille, Anna Jansana, Quan Gan, Marie Breeur, Hansjörg Baurecht, Patricia Bohmann, Julian Konzok, Michael J. Stein, Christina C. Dahm, Nuno R. Zilhão, Lene Mellemkjær, Anne Tjønneland, Rudolf Kaaks, Verena Katzke, Elif Inan-Eroglu, Matthias B. Schulze, Giovanna Masala, Sabina Sieri, Vittorio Simeon, Giuseppe Matullo, Esther Molina-Montes, Pilar Amiano, María-Dolores Chirlaque, Alba Gasque, Joshua Atkins, Karl Smith-Byrne, Pietro Ferrari, Vivian Viallon, Antonio Agudo, Marc J. Gunter, Catalina Bonet, Heinz Freisling, Robert Carreras-Torres

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Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury by Moa Pontén, Oskar Flygare, Martin Bellander, Moa Karemyr, Jannike Nilbrink, Clara Hellner, Olivia Ojala, Johan Bjureberg

“…Adding clinician predictions to the random forest model did not improve accuracy. …”
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Predicting Postoperative Re-Tear of Arthroscopic Rotator Cuff Repair Using Artificial Intelligence on Imbalanced Data by Zhibin Zhang, Zhewei Zhang, Zhaoxiang Peng, Yihong Dong

“…Retears after rotator cuff surgery are a common complication. Accurate prediction of retear is essential to minimise the risk of retear. …”
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Real time machine learning prediction of next generation sequencing test results in live clinical settings by Grace Y. E. Kim, Matthew Schwede, Conor K. Corbin, Sajjad Fouladvand, Rondeep Brar, David Iberri, William Shomali, Jean S. Oak, Dita Gratzinger, Henning Stehr, Jonathan H. Chen

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Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

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Development of a clinical predictive score for allergic reactions during oral food challenges in pediatric patients. by Manatchanok Pattarakiatjaroen, Araya Yuenyongviwat, Pasuree Sangsupawanich

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