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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Blockchain and explainable-AI integrated system for Polycystic Ovary Syndrome (PCOS) detection by Gowthami Jaganathan, Shanthi Natesan

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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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A Deep Learning-Based Framework for Bearing RUL Prediction to Optimize Laser Shock Peening Remanufacturing by Yuchen Liang, Yuqi Wang, Anping Li, Chengyi Gu, Jie Tang, Xianjuan Pang

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Predicting Nike Company Stock Price in Stock Market Using NARX Artificial Neural Network Method by Vajiheh Javani, Saeid Ahmadi Bonabi, Malihe Ashena

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A Prediction-Based Anomaly Detection Method for Traffic Flow Data with Multi-Domain Feature Extraction by Xianguang Jia, Jie Qu, Yingying Lyu, Mengyi Guo, Jinke Zhang, Fengxiang Guo

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Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

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Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction by Xinyue Lv, Youli Li, Lili Zhangzhong, Chaoyang Tong, Yibo Wei, Guangwei Li, Yingru Yang

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Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study by Damian Roland, Ewan Carr, Akash Deep, Sylvester Gomes, Harpreet Dhanoa, Phil Assheton

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PhotoModPlus: A web server for photosynthetic protein prediction from genome neighborhood features. by Apiwat Sangphukieo, Teeraphan Laomettachit, Marasri Ruengjitchatchawalya

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Predicting Bitcoin Prices Using Time Series Chaotic Neural Oscillatory Networks (TSCNON) in Quantum Finance by Lin Shiyu

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iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking. by Xuan Xiao, Jian-Liang Min, Pu Wang, Kuo-Chen Chou

“…In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. …”
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Enhancing CO2 emissions prediction for electric vehicles using Greylag Goose Optimization and machine learning by Ahmed El-Sayed Saqr, Mohamed S. Saraya, El-Sayed M. El-Kenawy

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