Global trends in machine learning applications for single-cell transcriptomics research by Xinyu Liu, Zhen Zhang, Chao Tan, Yinquan Ai, Hao Liu, Yuan Li, Jin Yang, Yongyan Song

“…Research hotspots concentrated on random forest (RF) and deep learning models, showing transition from algorithm development to clinical applications (e.g., tumor immune microenvironment analysis). …”
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A cross-sectional study of evaluating cervical spondylotic myelopathy based on gait and plantar pressures by Xuhong Zhang, Zichuan Wu, Hanlin Song, Aochen Xu, Junbin Liu, Junzhe Sheng, Baifeng Sun, Min Qi, Chen Xu, Yang Liu

“…Although previous studies have objectively assessed CSM-specific gait patterns using motion cameras as well as mechanical platforms, these methods have limitations such as limited metrics that can be analyzed or inconvenience for simple screening. Therefore, there is a need to develop effective screening methods. …”
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Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach by Mehewish Musheer Sheikh, Mamatha Balachandra, Narendra V. G., Arun G. Maiya

“…An automated image processing algorithm segmented plantar pressure images into forefoot and hindfoot regions for precise pressure distribution measurement. …”
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An Automatic Measurement Method of Test Beam Response Based on Spliced Images by Dong Liang, Jing Liu, Lida Wang, Chenjing Liu, Jia Liu

“…Next, the spliced image is obtained through the PCA-SIFT method with a screening mechanism. The cracks’ information is acquired by the dual network model. …”
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Callback time preference for prescreening visits among Black residents in the Boston area: findings from two randomized controlled trials by Ruth Zeto, Oluwagbemisola Ibikunle, Jingyi Cao, Hannah Col, Dhrumil Patil, Ruth-Alma Turkson-Ocran, Mingyu Zhang, Timothy B. Plante, Stephen P. Juraschek

“…Staff call attempts and participant screening status were logged prospectively. Gender was estimated based on first name, using a published algorithm. …”
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The Value of Subclinical Carotid Atherosclerosis for Primary Prevention of Cardiovascular Diseases. Review of the Main International Studies by E. K. Butina, E. V. Bochkareva

“…Measures for the prevention of cardiovascular diseases (CVD) are more effective if they are performed taking into account the risk factors of their development. …”
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Autism in the Faroe Islands: Diagnostic Stability from Childhood to Early Adult Life by Eva Kočovská, Eva Billstedt, Asa Ellefsen, Hanna Kampmann, I. Carina Gillberg, Rannvá Biskupstø, Guðrið Andorsdóttir, Tormóður Stóra, Helen Minnis, Christopher Gillberg

“…Stability of the DISCO algorithm subcategory diagnoses was more variable but still good for AD. …”
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Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo, Jianying Sun

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to screen three color-sensitive dyes that are more sensitive to changes in lactic acid content of maize silage. …”
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Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers by Cunen Wu, Cunen Wu, Cunen Wu, Cunen Wu, Weiwei Xue, Yuwen Zhuang, Dayue Darrel Duan, Dayue Darrel Duan, Zhou Zhou, Zhou Zhou, Xiaoxiao Wang, Zhenfeng Wu, Jin-yong Zhou, Xiangkun Huan, Ruiping Wang, Haibo Cheng, Haibo Cheng

“…This approach also aims to develop more accurate prediction models and therapeutic interventions, thereby helping more patients benefit from immunotherapy.…”
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Immunoglobulin G N-Glycosylation and Inflammatory Factors: Analysis of Biomarkers for the Diagnosis of Moyamoya Disease by Zan X, Liu C, Wang X, Sun S, Li Z, Zhang W, Sun T, Hao J, Zhang L

“…This research aimed to evaluate the diagnostic efficacy of IgG N-glycosylation for MMD.Methods: Ultra-high-performance liquid chromatography (UPLC) was employed to examine the properties of IgG N-glycans in blood samples from 116 patients with MMD and 126 controls, resulting in the quantitative determination of 24 initial glycan peaks (GP). Through the Lasso algorithm and multivariate logistic regression analysis, we constructed a diagnostic model based on initial glycans and related inflammatory factors to distinguish MMD patients from healthy individuals.Results: After adjusting for potential confounding variables, including age, fasting blood glucose (FBG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), neutrophil count (NEUT), and lymphocyte count (LYM), our study demonstrated significant differences in the characteristics of 6 initial glycans and 16 derived glycans between the MMD cohort and the healthy control group. …”
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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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Leveraging diverse cell-death patterns to predict to predict prognosis and immunotherapy in hepatocellular carcinoma by Xiaoxiang Zhang, Dongxiao Ding, Dianqian Wang, Yunsheng Qin

“…Although many efforts have been made to improve the prognosis of LIHC, the situation is still dismal. …”
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Diagnostic Value of Glycosylated Extracellular Vesicle microRNAs in Gastric Cancer by Wang S, Ma C, Ren Z, Zhang Y, Hao K, Liu C, Xu L, He S, Zhang J

“…The signatures were screened in a discovery cohort of GC patients (n=55) and non-disease controls (n=46) using an integrated process, including high-throughput sequencing technology, screening using a complete bioinformatics algorithm, validation using RT-qPCR, and evaluation by constructing a diagnostic model. …”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Compared with the three algorithms and error analysis, the effectiveness of the model and the two-stage algorithm was verified. …”
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Optimization of the Canopy Three-Dimensional Reconstruction Method for Intercropped Soybeans and Early Yield Prediction by Xiuni Li, Menggen Chen, Shuyuan He, Xiangyao Xu, Panxia Shao, Yahan Su, Lingxiao He, Jia Qiao, Mei Xu, Yao Zhao, Wenyu Yang, Wouter H. Maes, Weiguo Liu

“…Point cloud preprocessing was refined through the application of secondary transformation matrices, color thresholding, statistical filtering, and scaling. Key algorithms—including the convex hull algorithm, voxel method, and 3D α-shape algorithm—were optimized using MATLAB, enabling the extraction of multi-dimensional canopy parameters. …”
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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

“…Comparisons were made with a multilayer perceptron and two machine learning models of random forest and eXtreme Gradient Boosting (XGBoost). …”
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Keypoint Detection Based on Curvature Grouping and Adaptive Sampling by Bifu Li, Yu Cheng, Weitong Li

“…In the keypoint detection algorithm, the farthest point sampling methods and random sampling methods are usually used to select candidate points, then keypoints are screened out from the neighborhood of the candidate points. …”
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Ways to predict interstitial lung disease in patients with systemic sclerosis: results of an observational study by D. V. Khorolsky, A. A. Klimenko, E. S. Pershina, N. M. Babadeva, A. A. Kondrashov, N. A. Shostak, E. P. Mikheeva, E. V. Zhilyaev

“…It is advisable to include these indicators in the algorithm for screening and monitoring patients with SSc.…”
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Potential Metabolic Markers in the Tongue Coating of Chronic Gastritis Patients for Distinguishing Between Cold Dampness Pattern and Damp Heat Pattern in Traditional Chinese Medici... by Yuan S, Zhang R, Zhu Z, Zhou X, Zhang H, Li X, Hao Y

“…We applied metabolomics to identify differential metabolites distinguishing these patterns.Methods: In this study, the first principal component was analyzed by the OPLS-DA model. The model quality was evaluated by 7-fold cross-validation, and the model validity was evaluated based on R²Y (interpretability of categorical variable Y) and Q² (predictability of the model), and the permutation test was used for further verification. …”
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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

“…In this paper, we take breast cancer as the research object, and pioneer a hybrid strategy to process the data, and combine the machine learning method to build a more accurate and efficient breast cancer auxiliary diagnosis model. …”
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