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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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Despite these innovations, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain. …”
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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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Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

“…Insomnia, the most prevalent sleep disorder, requires more effective diagnosis and screening for proper treatment. …”
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Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…The risk of getting infected is a function of numerous factors where mathematical modeling would not yield fruitful results. However, a comprehensive analysis of these factors integrated with AI techniques, can offer a more precise and reliable prevision of individual risk profiles. …”
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Accurate and rapid single nucleotide variation detection in PCSK9 gene using nanopore sequencing by Ilaria Massaiu, Vincenza Valerio, Valentina Rusconi, Valentina Rusconi, Francesca Bertolini, Donato De Giorgi, Veronika A. Myasoedova, Paolo Poggio, Paolo Poggio

“…Twelve subjects were analyzed using different sequencing flow cells, basecalling models, and SNV calling algorithms. Sanger sequencing served as the reference for performance validation. …”
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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review by Xi Wang, Yujia Zhou, Guangyu Zhou

“…Studies on diagnosis and assessment (37/79, 47%) primarily used GenAI models to detect depression and suicidality through text data. …”
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Research on implementation of interventions in tuberculosis control in low- and middle-income countries: a systematic review. by Frank Cobelens, Sanne van Kampen, Eleanor Ochodo, Rifat Atun, Christian Lienhardt

“…Evaluations of diagnostic and screening algorithms were more frequent (n = 19) but geographically clustered and mainly of non-comparative design. …”
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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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Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

“…We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. …”
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Machine learning in dentistry and oral surgery: charting the course with bibliometric insights by Shuangwei Liu, Yuquan Hao, Shijie Zhu, Liyao Wan, Zhe Yi, Zhichang Zhang

“…Moreover, challenges, such as data availability and security, algorithmic biases, and “black-box models”, must be addressed. …”
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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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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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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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