Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

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Research on a Rapid Three-Dimensional Compressor Flow Field Prediction Method Integrating U-Net and Physics-Informed Neural Networks by Chen Wang, Hongbing Ma

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Self-Supervised Drift-Resilient Classification for Time Series Industrial Anomaly Detection by Myung-Kyo Seo, Byeong Hoon Yoon, Junseung Ryu, Hyung Ju Hwang

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Research on Storage Grain Temperature Prediction Method Based on FTA-CNN-SE-LSTM with Dual-Domain Data Augmentation and Deep Learning by Hailong Peng, Yuhua Zhu, Zhihui Li

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Hyperspectral imaging for one-step growth simulation of Brochothrix thermosphacta in chilled beef during storage by Xiaohua Liu, Binjing Zhou, Jin Song, Kang Tu, Jing Peng, Weijie Lan, Jing Xu, Jie Wu, Juqing Wu, Leiqing Pan

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Impact of Ki-67 and E-cadherin expression on lymphovascular invasion in upper urinary tract urothelial carcinoma by Stojnev Slavica, Krstić Miljan, Janković-Veličković Ljubinka, Ristić-Petrović Ana, Milojković Maja, Jovanović Ivan, Stokanović Dragana, Ugrenović Slađana

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Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review by Tianyi Liu, Andrew J. Krentz, Zhiqiang Huo, Vasa Ćurčin

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External validation of the Oncotype DX breast cancer recurrence score nomogram and development and validation of a novel machine learning-based model to predict postoperative overa... by Dongdong Wang, Xinfeng Wang, Xin Yang

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Machine Learning in Biomedical Informatics: Optimizing Resource Allocation and Energy Efficiency in Public Hospitals by Agostino Marengo, Vito Santamato, Massimo Iacoviello

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Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction by Min-Juan Zeng, Yan-Quan Liu, Ping Pang, Xiao-Jun Chen, He Huang, Rui-Na Huang, Shi-Sen Li, He-Hui Zhang, Yue Yin, Chang-Sen Wang, Jin-Da Lin, Lin Lin, Shao-Peng Chen, Li Xu, Liang-Qing Zhang

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Prediction of Excess Gibbs Free Energy for a New Working Pair CO2-[emim][Tf2N] in Absorption Refrigeration by He Lijuan, Zhu Chaoqun, Liang Jingjing

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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

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Leveraging LIME for Trustworthy Apple Quality Assessment by İsmail Kırbaş, Ahmet Çifci

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Advancing food security: The role of machine learning in pathogen detection by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Clinton Emeka, Phemelo Tamasiga, Gu Pang, Zainab Al-sharify

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First trimester hepatic steatosis index as a predictor of gestational diabetes mellitus: a cohort study in Northwestern China by Xuhui Liu, Xuegang Dai, Zhiru Guo, Rui Ma, Fei Li, Ling Zhang, Yining Liu, Lixia Liang, Jian He, Yanxia Wang

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A data mining approach for proposing a relationship to predict self-compaction concrete crack width after the self-healing period by Saeid Hosseini, Ali Seyedkazemi, Abdullah Davoudi-Kia, Saman Soleimani Kutanaei

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Calculation of Sensitivity and Specificity from Partial Data for Meta-Analyses: Introducing Some Practical Methods by Reihanesadat Khatami, Mohammadsadegh Faghihi, Hannanesadat Khatami, Mahmoud Yousefifard, Seyedhesamoddin Khatami

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Identification of temporal anomalies of spectrograms of vibration measurements of a turbine generator rotor using a recurrent neural network autoencoder by V. P. Kulagin, D. A. Akimov, S. A. Pavelyev, E. O. Guryanova

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Prediction of the Calorific Value and Moisture Content of <i>Caragana korshinskii</i> Fuel Using Hyperspectral Imaging Technology and Various Stoichiometric Methods by Xuehong De, Haoming Li, Jianchao Zhang, Nanding Li, Huimeng Wan, Yanhua Ma

“…Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msubsup><mrow><mi>R</mi></mrow><mrow><mi>P</mi></mrow><mrow><mn>2</mn></mrow></msubsup><mo>)</mo></mrow></semantics></math></inline-formula>, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. …”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

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