Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…Then, the accuracy of rock interface identification was analyzed using parameters such as penetration rate, revolution per minute, sound pressure level, and torque using the application of the change point detection algorithm, the strucchange model in RStudio software, and the decision tree algorithm. …”
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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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A FixMatch Framework for Alzheimer’s Disease Classification: Exploring the Trade-Off Between Supervision and Performance by Al Hossain, Umme Hani Konok, MD Tahsin, Raihan Ul Islam, Mohammad Rifat Ahmmad Rashid, Mohammad Shahadat Hossain, Karl Andersson

“…While experienced medical professionals can often identify AD through conventional assessment methods, limited resources and growing patient populations make large-scale and rapid screening increasingly necessary. In this work, we explore whether the FixMatch algorithm—a semi-supervised learning approach—can aid in classifying Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) by using the ADNI fMRI dataset of 5,182 images. …”
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Factors Influencing Misinformation Propagation: A Systemic Review by HAN Xi, LIAO Ke

“…This study constructs an integrated model of the influencing factors for misinformation propagation, which can provide direction for targeted interventions and algorithm design to mitigate the spread of misinformation. …”
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Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma by Shiyan Song, Wenfei Ge, Xiaochen Qi, Xiangyu Che, Qifei Wang, Guangzhen Wu

“…Radiomics features were screened using LASSO analysis. Eight ML algorithms were selected for diagnostic analysis of the test set. …”
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Artificial Intelligence in Biomedical Sciences: A Scoping Review by Rasha Abu-El-Ruz, Ali Hasan, Dima Hijazi, Ovelia Masoud, Atiyeh M. Abdallah, Susu M. Zughaier, Maha Al-Asmakh, Maha Al-Asmakh

“…Scope (6): Opportunities and limitations of AI in biomedical sciences, where major reported opportunities include efficiency, accuracy, universal applicability, and real-world application. Limitations include; model complexity, limited applicability, and algorithm robustness.ConclusionAI has generally been under characterized in the biomedical sciences due to variability in AI models, disciplines, and perspectives of applicability.…”
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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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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…The optimized model was integrated with structure-based virtual screening via molecular docking to prioritize repurposing candidate compounds. …”
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Semi-analytical BEM-FEM analysis of SDCM wall as passive wave barrier in saturated soil by Xiang Zhu, Gang Shi, Xinjun Gao, Hao Zhang, Song Wang, Guangyun Gao

“…And the model incorporates a parallel SPMD algorithm for efficiency and addresses corner discontinuities using a multi-value-node method. …”
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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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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…The Boruta algorithm was used for feature selection, and model performance was evaluated using cross-validation and a validation set. …”
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Deep learning system for the auxiliary diagnosis of thyroid eye disease: evaluation of ocular inflammation, eyelid retraction, and eye movement disorder by Yu Han, Jun Xie, Xiaoyu Li, Xinying Xu, Bin Sun, Han Liu, Chunfang Yan

“…The designed quantitative algorithm provides greater interpretability than existing studies, thereby validating the effectiveness of the diagnostic system.ConclusionThe deep learning-based auxiliary diagnostic model for TED established in this study exhibits high accuracy and interpretability in the diagnosis of ocular inflammation related to CAS, eyelid retraction, and eye movement disorders. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…AI has the ability to provide more precise disease identification and treatment strategies through efficient image analysis, multimodal data fusion, and deep learning algorithms. …”
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An Upper Partial Moment Framework for Pathfinding Problem Under Travel Time Uncertainty by Xu Zhang, Mei Chen

“…Theoretical analysis shows that the MUPM framework is consistent with the expected utility theory (EUT) and stochastic dominance theory (SDT), providing a behavioral foundation for the model. To efficiently solve the model, an SDT-based label-correcting algorithm is adapted, with a pre-screening step to reduce unnecessary pairwise path comparisons. …”
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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…After feature screening, 10 factors were selected for the prediction 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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Photon Counting Based on Solar-Blind Ultraviolet Intensified Complementary Metal-Oxide-Semiconductor (ICMOS) for Corona Detection by Yan Wang, Yunsheng Qian, Xiangyu Kong

“…Through experiments with an UV light source, the algorithm based on temporal resolution is proved to be more accurate. …”
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Increasing comprehensiveness and reducing workload in a systematic review of complex interventions using automated machine learning by Olalekan A Uthman, Rachel Court, Jodie Enderby, Lena Al-Khudairy, Chidozie Nduka, Hema Mistry, GJ Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…Background As part of our ongoing systematic review of complex interventions for the primary prevention of cardiovascular diseases, we have developed and evaluated automated machine-learning classifiers for title and abstract screening. The aim was to develop a high-performing algorithm comparable to human screening. …”
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Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study by Ting Peng, Rujia Miao, Hao Xiong, Yanhui Lin, Duzhen Fan, Jiayi Ren, Jiangang Wang, Yuan Li, Jianwen Chen

“…In the test group, all AUC were also greater than 0.80. The LightGBM model showed the best IR prediction performance with an accuracy of 0.7542, sensitivity of 0.6639, specificity of 0.7642, F1 ConclusionBy leveraging low-cost laboratory indicators and questionnaire data, the LightGBM model effectively predicts IR status in nondiabetic individuals, aiding in large-scale IR screening and diabetes prevention, and it may potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.…”
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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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