Student knowledge tracking based multi-indicator exercise recommendation algorithm by Bin ZHUGE, Zhenghu YIN, Wenxue SI, Lei YAN, Ligang DONG, Xian JIANG

“…Personalized exercise recommendation was an important topic in the era of education informatization, the forgetting laws of students in the learning process were ignored by the traditional problem recommendation algorithm, which failed to fully tap the students’ knowledge mastery level and the common characteristics of similar students, insufficient, could not reasonably promote students’ learning of new knowledge or help students find and fill omissions.In view of the above defects, a multi-index exercise recommendation method based on student knowledge tracking was proposed, which was divided into two modules: preliminary screening and re-filtering of exercises, focusing on the novelty, difficulty and diversity of exercise recommendation.Firstly, a knowledge probability prediction (SF-KCCP) model combined with students’ forgetting law was constructed to ensure the novelty of the recommended exercises.Then, students’ knowledge and concept mastery level was accurately excavated based on the dynamic key-value knowledge tracking (DKVMN) model to ensure that exercises of appropriate difficulty were recommended.Finally, the user-based collaborative filtering (UserCF) algorithm was integrated into the re-filtering module, and the similarity between student groups was used to achieve the diversity of recommendation results.The proposed method is demonstrated by extensive experiments to achieve better performance than some existing baseline models.…”
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Student knowledge tracking based multi-indicator exercise recommendation algorithm by Bin ZHUGE, Zhenghu YIN, Wenxue SI, Lei YAN, Ligang DONG, Xian JIANG

“…Personalized exercise recommendation was an important topic in the era of education informatization, the forgetting laws of students in the learning process were ignored by the traditional problem recommendation algorithm, which failed to fully tap the students’ knowledge mastery level and the common characteristics of similar students, insufficient, could not reasonably promote students’ learning of new knowledge or help students find and fill omissions.In view of the above defects, a multi-index exercise recommendation method based on student knowledge tracking was proposed, which was divided into two modules: preliminary screening and re-filtering of exercises, focusing on the novelty, difficulty and diversity of exercise recommendation.Firstly, a knowledge probability prediction (SF-KCCP) model combined with students’ forgetting law was constructed to ensure the novelty of the recommended exercises.Then, students’ knowledge and concept mastery level was accurately excavated based on the dynamic key-value knowledge tracking (DKVMN) model to ensure that exercises of appropriate difficulty were recommended.Finally, the user-based collaborative filtering (UserCF) algorithm was integrated into the re-filtering module, and the similarity between student groups was used to achieve the diversity of recommendation results.The proposed method is demonstrated by extensive experiments to achieve better performance than some existing baseline models.…”
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Preoperative prediction of recurrence risk factors in operable cervical cancer based on clinical-radiomics features by Xue Du, Xue Du, Chunbao Chen, Lu Yang, Yu Cui, Min Li

“…Logistic regression algorithms were used to construct a fusion clinical-radiomics model to visualize nomograms. …”
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Two-test algorithms for infectious disease diagnosis: Implications for COVID-19. by Sunil Pokharel, Lisa J White, Jilian A Sacks, Camille Escadafal, Amy Toporowski, Sahra Isse Mohammed, Solomon Chane Abera, Kekeletso Kao, Marcela De Melo Freitas, Sabine Dittrich

“…A two-test algorithm comprising a rapid screening test followed by confirmatory laboratory testing can reduce false positive rate, produce rapid results and conserve laboratory resources, but can lead to large number of missed cases in high prevalence setting. …”
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Development of a machine learning prognostic model for early prediction of scrub typhus progression at hospital admission based on clinical and laboratory features by Youguang Lu, Zixu Wang, Junhu Wang, Yingqing Mao, Chuanshen Jiang, Jinpiao Wu, Haizhou Liu, Haiming Yi, Chao Chen, Wei Guo, Liguan Liu, Yong Qi

“…Eighteen objective clinical and laboratory features collected at admission were screened using various feature selection algorithms, and used to construct models based on six machine learning algorithms.Results The model based on Gradient Boosting Decision Tree using 14 features screened by Recursive Feature Elimination was evaluated as the optimal one. …”
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Pulmonary Nodules Detection Algorithm Combining Multi-view and Attention Mechanism by LIU Yu-bo, LIU Guo-zhu, SHI Cao, XU Can-hui

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Panel defect detection algorithm based on improved Faster R-CNN by Chen Wanqin, Tang Qingshan, Huang Tao

“…Experimental results show that the accuracy and recognition rate of the optimized network model have been greatly improved.…”
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DETECTION OF Β THALASSEMIA CARRIERS BY RED CELL PARAMETERS OBTAINED FROM AUTOMATIC COUNTERS USING MATHEMATICAL FORMULAS by Idit Lachover Roth, Boaz Lachover, Guy Koren, Carina Levin, Luci Zalman, Ariel Koren

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Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine learning by Changjin Wei, Yongfeng Zhu, Caiming Chen, Feipeng Li, Li Zheng

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”
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Socially Responsible Investment Portfolio Construction with a Double-Screening Mechanism considering Machine Learning Prediction by Jun Zhang, Xuedong Chen

“…The proposed models consist of two stages, i.e., stock screening and asset allocation. …”
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Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension by Wei Zhao, Zhihua Huang, Xiaolin Diao, Zhan Yang, Zhihui Zhao, Yun Xia, Qing Zhao, Zhaohong Sun, Qunying Xi, Yanni Huo, Ou Xu, Jiahui Geng, Xin Li, Anqi Duan, Sicheng Zhang, Luyang Gao, Yijia Wang, Sicong Li, Qin Luo, Zhihong Liu

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Predicting algorithm of attC site based on combination optimization strategy by Zhendong Liu, Xi Chen, Dongyan Li, Xinrong Lv, Mengying Qin, Ke Bai, Zhiqiang He, Yurong Yang, Xiaofeng Li, Qionghai Dai

“…Based on the structural features of attC sites, the prediction algorithm realises the high-precision prediction of the recombination frequencies between sites and the screening of the top 20 important features that play a role in recombination, which are effective for improving the design method of attC sites. …”
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Characterization of lactylation modification subtypes and the promoting role of CCL20 in hepatocellular carcinoma progression by Li-Hong Wu, Liu Yang, Xiang-Xu Wang, Shuang Bai, Xi Yan, Jing Wei, Jun Wang, Fei Tian

“…The CIBERSORT algorithm was utilized to analyze immune cell infiltration. …”
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MLP-UNet: an algorithm for segmenting lesions in breast and thyroid ultrasound images by Tian-feng Dong, Chang-jiang Zhou, Zhen-yi Huang, Hao Zhao, Xue-long Wang, Shi-ju Yan

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Glypican-3 regulated epithelial mesenchymal transformation-related genes in osteosarcoma: based on comprehensive tumor microenvironment profiling by Jiaming Zhang, Wei Wang

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to screen candidate genes for developing a prognostic model. …”
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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning by Jiao Qiu, Yalin Xu, Luyuan Tong, Xingchun Yang, Xiao Wu

“…Subsequently, functional enrichment analysis was performed to clarify the biological functions of these genes. Machine learning algorithms were used to screen for the hub RA-RF differential expression genes, and then a Logistic Regression (LR) model was constructed. …”
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Genome-wide expression in human whole blood for diagnosis of latent tuberculosis infection: a multicohort research by Fan Jiang, Fan Jiang, Fan Jiang, Yanhua Liu, Linsheng Li, Linsheng Li, Ruizi Ni, Ruizi Ni, Yajing An, Yajing An, Yufeng Li, Yufeng Li, Lingxia Zhang, Wenping Gong

“…A Naive Bayes (NB) model incorporating these two markers demonstrated robust diagnostic performance: training set AUC: median = 0.8572 (inter-quartile range 0.8002, 0.8708), validation AUC = 0.5719 (0.51645, 0.7078), and subgroup AUC = 0.8635 (0.8212, 0.8946).ConclusionOur multicohort analysis established an NB-based diagnostic model utilizing S100A12/S100A8, which maintains diagnostic accuracy across diverse geographic, ethnic, and clinical variables (including HIV co-infection), highlighting its potential for clinical translation in LTBI/ATB differentiation.…”
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High-throughput screening and machine learning classification of van der Waals dielectrics for 2D nanoelectronics by Yuhui Li, Guolin Wan, Yongqian Zhu, Jingyu Yang, Yan-Fang Zhang, Jinbo Pan, Shixuan Du

“…Here, we employed a topology-scale algorithm to screen vdW materials consisting of zero-dimensional (0D), one-dimensional (1D), and 2D motifs from Materials Project database. …”
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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm by Hongyan Wang

“…In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated.…”
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Birdsong Recognition Based on Attention Hash Algorithm Combined with Contrastive Loss by WANG Yuwei, CHEN Aibin, ZHOU Guoxiong, ZHANG Zhiqiang

“…Aiming at the problems of length misalignment, redundancy, noise and large intra-class differences in birdsong data collected in the natural environment, an automatic birdsong recognition model composed of a two-stage hash algorithm based on multi- level attention and a lightweight classifier based on fusion contrastive loss is proposed. …”
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