Development and Evaluation of a Machine Learning Model for Predicting 30-Day Readmission in General Internal Medicine by Abdullah M. Al Alawi, Mariya Al Abdali, Al Zahraa Ahmed Al Mezeini, Thuraiya Al Rawahia, Eid Al Amri, Maisam Al Salmani, Zubaida Al-Falahi, Adhari Al Zaabi, Amira Al Aamri, Hatem Al Farhan, Juhaina Salim Al Maqbali

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Modeling Age-to-Age Development Factors in Auto Insurance Through Principal Component Analysis and Temporal Clustering by Shengkun Xie, Chong Gan

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Dual statistical models link baseline visual attention measure to risk for significant symptomatic concussion in sports by Lisa A Spielman, Jun Maruta, Jamshid Ghajar

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Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples by Eda Yilmaz, Hacer Yalim Keles

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A Cluster‐Based Deep Learning Model Perceiving Series Correlation for Accurate Prediction of Phonon Spectrum by Chao Liang, Yilimiranmu Rouzhahong, Shunwei Yao, Junhao Liang, Chunlin Yu, Biao Wang, Huashan Li

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MATLAB-empowered brightness defect prediction system in pulp processing bleaching stage: An empirical modelling approach by Michael, M. Thoriq Al Fath, Vikram Alexander, Gina Cynthia Raphita Hasibuan, Muhammad Syukri, Muhammad Hendra S. Ginting, Rivaldi Sidabutar, Nisaul Fadilah Dalimunthe

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Prediction of coal and gas outbursts based on physics informed neural networks and traditional machine learning models by Lei Wang, Baoshan Jia, Guorui Su

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A scoring system with high predictive performance for poor outcomes in acute carbon monoxide poisoning by Hidetaka Onda, Takuya Nishino, Mizuki Kojima, Nodoka Miyake, Kenta Shigeta, Naoki Tominaga, Shoji Yokobori

“…In this study, we aimed to develop a clinical scoring model to predict poor outcomes in acute CO poisoning cases. …”
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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

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Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension by Anhua Cao, You Nie, Zhun Zhong, Yi Pei, Yi Pei, Ping Deng, Hebin Xie, Yiping Leng, Yiping Leng

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Adaptive regulation of a non inverting buck boost converter with Levenberg Marquardt based sliding mode predictive control scheme by Omid Asvadi-Kermani, Hoda Sorouri, Arman Oshnoei

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A novel satisfactory model predictive control based on current variance for high power three‐level‐NPC rectifiers by Bo Yang, Zhikang Guo, Zongbin Ye, Jiayi Kong, Guojun Tan

“…Abstract Here, a novel satisfactory model predictive control based on current variance (CV‐SMPC) is proposed for three level neutral point clamped (NPC) rectifiers. …”
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Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms by Yuyang Chen, Jiansheng Zhong, Haixiang Li, Kunzhe Lin, Liangfeng Wei, Shousen Wang

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Construction and validation of tertiary models for predicting growth of Salmonella Infantis in chicken liver during a processing chain deviation by Thomas P. Oscar

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Modeling the growth of Bacillus cereus in Napa cabbage (Brassica rapa subsp. pekinensis) across different sea salt concentrations by Eun Bi Jeon, Sung-Hee Park, Shin Young Park

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Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context by Yaxi Cui, Jing Zhang, Yuwen Wang, Ying Liao, Keyu Liu, Wenrui Xu, Shu Wu, Chufan Sun, Chunyu Zhang, Qingyou Zhang, Ping Liu, Yuli Wang, Yanjun Deng, Chen Shen, Yao Lin, Hong Cai, Juan Zhang, Runmei Zou, Ping Liu, Shuo Wang, Hongfang Jin, Lin Shi, Cheng Wang, Junbao Du

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Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm by Qianmei Yang, Cuifang Liu, Yongyue Wang, Guifang Dong, Jinghuan Sun

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Predictive modeling of ultimate tensile strength in dissimilar friction stir welded aluminum alloys via machine learning approach by Meghavath Mothilal, Atul Kumar

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BAYESIAN NEURAL NETWORK RAINFALL MODELLING: A CASE STUDY IN EAST JAVA by Suci Astutik, Nur Silviyah Rahmi, Diego Irsandy, Fang You Dwi Ayu Shalu Saniyawati, Fidia Raaihatul Mashfia, Evelin Dewi Lusiana, Intan Fadhila Risda, Mohammad Hilmi Susanto

“…ANN is suitable for rainfall models that have intermittent characteristics. Meanwhile, the Bayesian method provides advantages in producing model parameter inferences that provide uncertainty measurements in predictions. …”
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