A real-world Pharmacovigilance study of brodalumab based on the FDA adverse event reporting system by Ke He, Kaidi Zhao, Tingyi Yin, Meng Liu, Jiashu Liu, Wenqian Du, Xinyi Liu, Baochen Cheng, Dewu Zhang, Yan Zheng

“…Techniques such as the Reporting Odds Ratio, Proportional Reporting Ratio, Multi-item Gamma Poisson Shrinker, and Bayesian Confidence Propagation Neural Network were utilized to analyze the adverse events associated with brodalumab. …”
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Machine learning-based study of hardness in polypropylene/carbon nanotube and low-density polyethylene/carbon nanotube composites by Harshit Sharma, Gaurav Arora, Raj Kumar, Suman Debnath, Suchart Siengchin

“…(Random Forest, Support Vector Regression, K-Nearest Neighbors, Linear Regression, and Neural Network). Four input vectors have been used in the construction of proposed network, such as CNT concentration, power, pressure applied, and exposure time. …”
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Automatic detection, identification and counting of deep-water snappers on underwater baited video using deep learning by Florian Baletaud, Florian Baletaud, Florian Baletaud, Sébastien Villon, Antoine Gilbert, Jean-Marie Côme, Sylvie Fiat, Corina Iovan, Laurent Vigliola

“…To address this issue, we used a Region-based Convolutional Neural Network (Faster R-CNN), a deep learning architecture to automatically detect, identify and count deep-water snappers in BRUVS. …”
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Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification by Yasser Abduallah, Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang, Vania K. Jordanova, Vasyl Yurchyshyn, Huseyin Cavus, Ju Jing

“…Abstract We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based on 1‐ and 5‐min resolution data. …”
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Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database by Xi-Feng Wang, Lu-Ri Bao, Ta-La Hu, Rui-Feng Xu, Wu-Niri Gao, Jing-Yuan Wang, Jian-Rong Zhao, Zhen-Li Fu, Shu-Fang Wang, Yan Meng

“…The current study was conducted to assess real-world adverse events (AEs) associated with eculizumab through data mining of the FDA Adverse Event Reporting System (FAERS).MethodsDisproportionality analyses, including Reporting Ratio Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms were used to quantify the signals of eculizumab-associated AEs.ResultsA total of 46,316 eculizumab-related ADEs reports were identified by analyzing 19,418,776 reports in the U.S. …”
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A study on the pharmacovigilance of various SGLT-2 inhibitors by Yanwen Dong, Yangyang Wang, Yangyang Wang, Xiaomei Lan, Xiaomei Lan, Huiyan Zeng, Huiyan Zeng

“…Four signal detection metrics—reporting odds ratio (ROR), proportional reporting ratios (PRRs), Bayesian Confidence Propagation Neural Network (BCPNN), and empirical Bayesian geometric mean (EBGM)—were utilized to infer ADRs and assess differences among specific SGLT2i drugs through intersection analysis.ResultsExcept for canagliflozin, both dapagliflozin and empagliflozin showed a general increase in ADRs. …”
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Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles by Adeel Khan, Adeel Khan, Haroon Khan, Nongyue He, Zhiyang Li, Heba Khalil Alyahya, Yousef A. Bin Jardan

“…To transform the qualitative colorimetric approach into a quantitative operation, we developed an intelligent convolutional neural network (CNN)-powered quantitative analyzer for chromaticity in the form of a smartphone app named ExoP, thereby achieving the intelligent analysis of chromaticity with minimal user intervention or additional hardware attachments for the sensitive and specific quantification of PD-L1@EVs. …”
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Linear IgA bullous dermatosis secondary to drugs: a real-world pharmacovigilance study of the FDA adverse event reporting system by Yixuan Yang, Hanzhang Xie, Shuhan Liu, Ying Jia, Bingnan Cui, Zhanshuo Xiao

“…The Reporting Odds Ratio, Proportional Reporting Ratio, Bayesian Confidence Propagation Neural Network, and Empirical Bayes Geometric Mean were calculated to assess the reported associations between available drugs and LABD. …”
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Analysis of Contact Position for Subthalamic Nucleus Deep Brain Stimulation-Induced Hyperhidrosis by Chunhui Yang, Yiqing Qiu, Xi Wu, Jiali Wang, Yina Wu, Xiaowu Hu

“…To analyze the hyperhidrosis neural network structure induced by subthalamic nucleus (STN) - deep brain stimulation (DBS). …”
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Profile to frontal face recognition in the wild using coupled conditional generative adversarial network by Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti, Nasser M. Nasrabadi

“…Additionally, the authors have also implemented a coupled convolutional neural network (cpCNN) and an adversarial discriminative domain adaptation network (ADDA) for profile to frontal FR. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…The approach uses a convolutional neural network to automatically detect wood. We sampled data to represent different wood transport conditions, combining 20 datasets to yield thousands of instream wood images. …”
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Predicting the exposure of mycophenolic acid in children with autoimmune diseases using a limited sampling strategy: A retrospective study by Ping Zheng, Ting Pan, Ya Gao, Juan Chen, Liren Li, Yan Chen, Dandan Fang, Xuechun Li, Fei Gao, Yilei Li

“…Ten algorithms, including Random Forest, XGBoost, LightGBM, Gradient Boosting Decision Tree, CatBoost, Artificial Neural Network, Grandient Boosting Machine, Transformer, Wide&Deep, and TabNet, were employed for modeling based on two, three, or four concentrations of MPA. …”
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Magnetic field influence on heat transfer of NEPCM in a porous triangular cavity with a cold fin and partial heat sources: AI analysis combined with ISPH method by Munirah Aali Alotaibi, Weaam Alhejaili, Abdelraheem M. Aly, Samiyah Almalki

“…This study employs the Incompressible Smoothed Particle Hydrodynamics (ISPH) method and an Artificial Neural Network (ANN) model to examine the thermal and fluid dynamics behavior of nano-enhanced phase change material (NEPCM) within a triangular cavity containing a fin. …”
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Deep Ensemble Learning for Human Action Recognition in Still Images by Xiangchun Yu, Zhe Zhang, Lei Wu, Wei Pang, Hechang Chen, Zhezhou Yu, Bin Li

“…Firstly, we construct an end-to-end NCNN-based model by attaching the nonsequential convolutional neural network (NCNN) module to the top of the pretrained model. …”
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Skull vibration induced nystagmus, velocity storage and self-stability by Ian S. Curthoys, David S. Zee, Georges Dumas, Georges Dumas, Christopher J. Pastras, Julia Dlugaiczyk

“…Within the indirect pathway there is a unique neural mechanism called the velocity storage integrator (VSI) which is part of a neural network generating prolonged nystagmus, afternystagmus and the sensation of self-motion and its converse self-stability. …”
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ConvXGB: A novel deep learning model to predict recurrence risk of early-stage cervical cancer following surgery using multiparametric MRI images by Ji Wu, Jian Li, Bo Huang, Sunbin Dong, Luyang Wu, Xiping Shen, Zhigang Zheng

“…We designed a novel deep learning model called “ConvXGB” for predicting recurrence risk by combining the convolutional neural network (CNN) and eXtreme Gradient Boost (XGBoost). …”
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Adverse events in the nervous system associated with blinatumomab: a real-world study by Wen Gao, Jingwei Yu, Yifei Sun, Zheng Song, Xia Liu, Xue Han, Lanfan Li, Lihua Qiu, Shiyong Zhou, Zhengzi Qian, Xianhuo Wang, Huilai Zhang

“…The reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence interval progressive neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms were utilized for data mining. …”
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Effect of Molarity of Sodium Hydroxide on the Strength Behavior of Fiber-Reinforced Geopolymer Concrete Exposed to Elevated Temperature by Abbasali Saffar, Mohammad Ehsanifar, Seyed Mohammad Mirhoseini, Mohammad Javad Taheri Amiri

“…Beside, post-fire strength of FRGPC was predicted using artificial neural network (ANN) and support vector machines (SVM) with the integration of water cycle algorithm (WCA). …”
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Electricity Theft Detection Using Machine Learning in Traditional Meter Postpaid Residential Customers: A Case Study on State Electricity Company (PLN) Indonesia by Alief Pascal Taruna, Galih Arisona, Dwi Irwanto, Arif Bijak Bestari, Wildan Juniawan

“…Various classification models, including Decision Tree, Naive Bayes, Random Forest, K-Nearest Neighbors, Logistic Regression, and Deep Neural Network, were evaluated, with Random Forest achieving the best performance across simulations. …”
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Displacement Prediction of a Complex Landslide in the Three Gorges Reservoir Area (China) Using a Hybrid Computational Intelligence Approach by Junwei Ma, Xiaoxu Niu, Huiming Tang, Yankun Wang, Tao Wen, Junrong Zhang

“…The results show that the mean prediction interval widths of the proposed approach at ZG287 and ZG289 are 27.30 and 33.04, respectively, which are approximately 60 percent lower than that obtained using the traditional bootstrap-extreme learning machine-artificial neural network (Bootstrap-ELM-ANN). Moreover, the obtained point predictions show great consistency with the observations, with correlation coefficients of 0.9998. …”
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