Study on classification of aluminum plastic packaging tablets for drugs based on SOM-FDA using XRF spectroscopy(基于SOM-FDA利用XRF对药品铝塑包装片的分类) by 姜红(JIANG Hong), 康瑞雪(KANG Ruixue), 郝小辉(HAO Xiaohui)

“…The established classification model is scientifically accurate and can provide assistance for public security organs in large-scale screening, determining investigation directions, and shortening investigation time.…”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques by Mohammed Tareq Mutar, Jaffar Nouri Alalsaidissa, Mustafa Majid Hameed, Ali Almothaffar

“…BACKGROUND: Deep learning’s role in blood film screening is expanding, with recent advancements including algorithms for the automated detection of sickle cell anemia, malaria, and leukemia using smartphone images. …”
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Efficient secure federated learning aggregation framework based on homomorphic encryption by Shengxing YU, Zhong CHEN

“…In order to solve the problems of data security and communication overhead in federated learning, an efficient and secure federated aggregation framework based on homomorphic encryption was proposed.In the process of federated learning, the privacy and security issues of user data need to be solved urgently.However, the computational cost and communication overhead caused by the encryption scheme would affect the training efficiency.Firstly, in the case of protecting data security and ensuring training efficiency, the Top-K gradient selection method was used to screen model gradients, reducing the number of gradients that need to be uploaded.A candidate quantization protocol suitable for multi-edge terminals and a secure candidate index merging algorithm were proposed to further reduce communication overhead and accelerate homomorphic encryption calculations.Secondly, since model parameters of each layer of neural networks had characteristics of the Gaussian distribution, the selected model gradients were clipped and quantized, and the gradient unsigned quantization protocol was adopted to speed up the homomorphic encryption calculation.Finally, the experimental results show that in the federated learning scenario, the proposed framework can protect data privacy, and has high accuracy and efficient performance.…”
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Load identification method based on one class classification combined with fuzzy broad learning by Wang Yi, Wang Xiaoyang, Li Songnong, Chen Tao, Hou Xingzhe, Fu Xiuyuan

“…Considering the recognition rate and model complexity, the fuzzy broad learning system is used to classify and recognize the screened samples. …”
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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Multi-Dimensional Lithology Identification Method Based on Microresistivity Image Logging by LIU Juan, MIN Xuanlin, QI Zhongli, YI Jun, LAI Fuqiang, ZHOU Wei

“…For the electrical imaging color features of different resistivity responses (mudstone, calcareous mudstone and sandy mudstone), K-means++ algorithm is used to screen out the clustering centers of the overall distribution of the data set to achieve fast classification of the electro-imaging colors. …”
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Machine learning for clustering and classification of early knee osteoarthritis using single-leg standing kinematics by Ui-Jae Hwang, Kyu Sung Chung, Sung-Min Ha

“…This study investigated the application of machine learning techniques to single-leg standing (SLS) kinematics to classify and predict EOA. (1) To identify distinct groups based on SLS kinematic patterns using unsupervised learning algorithms, (2) to develop supervised learning models to predict EOA status, and (3) to identify the most influential kinematic variables associated with EOA. …”
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The Marine Safety Simulation based Electronic Chart Display and Information System by Xin Yu Zhang, Yong Yin, Jin YiCheng, XiaoFeng Sun, Ren HongXiang

“…The man-machine conversation method is taken to amend planned route to obtain autodeciding of feasibility according to ECDIS information, and the route monitoring algorithm is improved by enhancing its precision caused by screen coordinate conversion. …”
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Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy by Hua Chen, Kehui Mei, Yuan Zhou, Nan Wang, Guangxing Cai

“…Then, the features of the dataset are initially screened using the mutual information method, and further secondary feature selection is performed using the recursive feature elimination method based on the XGBoost algorithm. …”
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A comparative study of bone density in elderly people measured with AI and QCT by Min Guo, Min Guo, Yu Zhang, Yu Zhang, XinXin Gu, XinXin Gu, Xuhui Liu, Xuhui Liu, Fei Peng, Fei Peng, Zongjun Zhang, Zongjun Zhang, Mei Jing, Mei Jing, Yingxia Fu, Yingxia Fu

“…Early detection of reduced bone mineral density (BMD) through opportunistic screening is critical for preventing fragility fractures. …”
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Polygraph and audio synchronization applied to apnea event analysis based on non-negative matrix factorization by Francisco David Gonzalez-Martinez, Juan De La Torre-Cruz, Julio Jose Carabias-Orti, Francisco Jesus Canadas-Quesada, Alejandro Antonio Salvador-Navarro, Jose Ranilla, Lyam Lamrini-H. Laarbi

“…The proposed method introduces an iterative time-alignment algorithm based on the cross-correlation between an estimated respiratory sound signal and the nasal flow signal from PG. …”
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Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

“…In conclusion, based on the winter wheat ChD data set and the corresponding canopy hyperspectral data set, combined with 3 FOD calculation methods, 1 band screening method, and 8 modeling algorithms, this study constructed hyperspectral monitoring models for winter wheat ChD. …”
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Hydraulic Pump Fault Diagnosis Method Based on EWT Decomposition Denoising and Deep Learning on Cloud Platform by Wanlu Jiang, Zhenbao Li, Sheng Zhang, Teng Wang, Shuqing Zhang

“…An axial piston pump fault diagnosis algorithm based on empirical wavelet transform (EWT) and one-dimensional convolutional neural network (1D-CNN) is presented. …”
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The Effect of Arctic Sea‐Ice Loss on Extratropical Cyclones by Stephanie Hay, Matthew D. K. Priestley, Hao Yu, Jennifer L. Catto, James A. Screen

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Characterization of the salivary microbiome in healthy individuals under fatigue status by Xianhui Peng, Na Han, Yanan Gong, Lihua He, Yanli Xu, Di Xiao, Tingting Zhang, Yujun Qiang, Xiuwen Li, Wen Zhang, Jianzhong Zhang

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”
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Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy by Zhi Chen, GuangMing Yi, XinYan Li, Bo Yi, XiaoHui Bao, Yin Zhang, XiaoYue Zhang, ZhenZhou Yang, Zhengjun Guo

“…By selecting multiple machine learning algorithm frameworks and competing for the best combination model based on research goals, the reliability and accuracy of the radiation pneumonitis prediction model can be greatly improved. …”
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Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer by Peng Zhang, Meizhong Qin, Fen Li, Kunpeng Hu, He Huang, Cuicui Li

“…Abstract Background Thyroid cancer (THCA) exhibits high molecular heterogeneity, posing challenges for precise prognosis and personalized therapy. Most existing models rely on single-omics data and limited algorithms, reducing robustness and clinical value. …”
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Diagnosing facial synkinesis using artificial intelligence to advance facial palsy care by Leonard Knoedler, Christian Festbaum, Jillian Dean, Helena Baecher, Grégoire de Lambertye, Maximilian Maul, Thomas Schaschinger, Tobias Niederegger, Alexandra Scheiflinger, Michael Alfertshofer, Khalil Sherwani, Claudius Steffen, Max Heiland, Steffen Koerdt, Samuel Knoedler, Andreas Kehrer

“…This study aimed to develop a cost-effective, rapid, and accurate artificial intelligence (AI)-based algorithm to screen FP patients for facial synkinesis. …”
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Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices by Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya

“…Methods This retrospective study uses data from patients in the medical ICU from 2015-to-2019 to develop ML models. The models were based on dynamic ICU-readily available features such as hourly vital signs, laboratory results, and interventions and were developed using various ML algorithms. …”
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