Association between impaired sensitivity to thyroid hormones and sedentary behavior: a cross-sectional study by Hangzhou Yang, Jie Kang, Lingkang Dong, Zihan Lin, Qixian Lin, Bo Wu

“…The Least Absolute Shrinkage and Selection Operator (LASSO) regression and the Boruta algorithm were employed to screen out confounding factors closely associated with sedentary time and the parametric thyroid feedback quantile-based index (PTFQI). …”
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Relationship between stress hyperglycemia ratio and the incidence of atrial fibrillation in patients after coronary artery bypass grafting: a retrospective study based on the MIMIC... by Runjia Liu, Jiatong Li, Jing Zeng, Yuxuan Tao, Dong Chen, Haixia Li

“…We employed logistic regression models, restricted cubic splines (RCS), threshold effect analysis, ubgroup analysis, Boruta algorithm, lasso algorithm, and receiver operating characteristics (ROC) to analyze the relationship between SHR and POAF incidence comprehensively. …”
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PRKDC regulates cGAMP to enhance immune response in lung cancer treatment by Zhanghao Huang, Zhanghao Huang, Zhanghao Huang, Runqi Huang, Runqi Huang, Runqi Huang, Jun Zhu, Jun Zhu, Youlang Zhou, Youlang Zhou, Jiahai Shi, Jiahai Shi

“…This study aimed to investigate the antitumor effects of 2’,3’-cGAMP in LUAD.MethodHerein, patients with LUAD were screened for prognostic biomarkers, which were then assessed for sensitivity to immunotherapy and chemotherapy utilizing the “TIDE” algorithm and CellMiner database. …”
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Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. …”
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Integrating Artificial Intelligence and Microfluidics Technology for Psoriasis Therapy: A Comprehensive Review for Research and Clinical Applications by Ibrahim Shaw, Yimer Seid Ali, Changhong Nie, Kexin Zhang, Chuanpin Chen, Yin Xiao

“…Integrating artificial intelligence (AI) with microfluidics promises to overcome these barriers by leveraging AI algorithms to automate device design, streamline experimentation, and enhance diagnostic and therapeutic outcomes. …”
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Big data transfer service architecture for cloud data centers: problems, methods, applications, and future trends by Muhammad Umar Majigi, Ismaila Idris, Shafi’i Muhammad Abdulhamid, Richard A. Ikuesan

“…Key issues identified in the context of big data transfer services for cloud data centers include storage, big data transfer, service transfer architecture, data processing, bandwidth, and security, all of which demand extensive research. After thoroughly screening selected peer-reviewed articles, the primary open issues are: incorporating a data placement module in the data transfer service, providing end-to-end safeguards for packet delivery, improving data transfer time and speed, minimizing costs and implementation overhead, ensuring secure data transfer between servers in the cloud, demonstrating effective big data transfer architectures, considering topology-specific extensions to reduce the busty nature of data centers, and enhancing data transfer services using machine learning algorithms during upload and download operations. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…We evaluate their performance on regression and optimization molecular tasks using docking scores, finding them to outperform classical single-task and transfer-learning models. We examine the issue of generalization to divergent test tasks, which is a general concern of meta-learning algorithms in science, and propose strategies to alleviate it.…”
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A Line Feature-Based Rotation Invariant Method for Pre- and Post-Damage Remote Sensing Image Registration by Yalun Zhao, Derong Chen, Jiulu Gong

“…First, we extract and screen straight line segments from the images before and after damage. …”
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Biophysical and nutritional combination treatment for myosteatosis in patients with sarcopenia: a study protocol for single-blinded randomised controlled trial by Maoyi Tian, Ling Qin, Simon Kwoon Ho Chow, Wing Hoi Cheung, A A Welch, Can Cui, Parco M Siu, Meng Chen Michelle Li, Yu Kin Cheng, Ronald Man Yeung Wong, Timothy CY Kwok, Minghui Yang, Clinton Rubin, Sheung Wai Law

“…The findings of this study will demonstrate the effect of combination treatment as an alternative for managing sarcopenia.Methods and analysis In this single-blinded randomised controlled trial, subjects will be screened based on the Asian Working Group for Sarcopenia (AWGS) 2019 definition. 200 subjects who are aged 65 or above and identified sarcopenic according to the AWGS algorithm will be recruited. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…This work compares and reports a classification of malware detection work based on deep learning algorithms. The 2011–2025 articles were considered, and the latest work focused on the literature for the 2018–2025 years; after screening, 72 articles were selected for the initial study. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…By integrating machine learning (ML) algorithms, such as Gradient Boosting Models and Support Vector Machines, with SHAP-based feature visualization, robust screening methods were applied to ensure the reliability of predictions. …”
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A portable retina fundus photos dataset for clinical, demographic, and diabetic retinopathy prediction by Chenwei Wu, David Restrepo, Luis Filipe Nakayama, Lucas Zago Ribeiro, Zitao Shuai, Nathan Santos Barboza, Maria Luiza Vieira Sousa, Raul Dias Fitterman, Alexandre Durao Alves Pereira, Caio Vinicius Saito Regatieri, Jose Augusto Stuchi, Fernando Korn Malerbi, Rafael E. Andrade

“…The mBRSET dataset serves as a resource for developing AI algorithms and investigating real-world applications, enhancing ophthalmological care in resource-constrained environments.…”
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Identification of M1 macrophage infiltration-related genes for immunotherapy in Her2-positive breast cancer based on bioinformatics analysis and machine learning by Sizhang Wang, Xiaoyan Wang, Jing Xia, Qiang Mu

“…Then, four overlapping M1 macrophage infiltration-related genes (M1 MIRGs), namely CCDC69, PPP1R16B, IL21R, and FOXP3, were obtained using five machine-learning algorithms. Subsequently, nomogram models were constructed to predict the incidence of Her2-positive breast cancer patients. …”
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Quality of care for severe acute malnutrition delivered by community health workers in southern Bangladesh by Chloe Puett, Jennifer Coates, Harold Alderman, Kate Sadler

“…CHWs screened children at community level using a mid‐upper arm circumference measurement, and treated cases without medical complications. …”
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Advancing Mn-based electrocatalysts: Evolving from Mn-centered octahedral entities to bulk forms by Huan Li, Jinchao Xu, Liyuan Yang, Wanying Wang, Bin Shao, Fangyi Cheng, Chunning Zhao, Weichao Wang

“…According to the catalytic requirements of an individual entity and its stacking modes, we further developed a search algorithm to identify three-dimensional (3D) structures from 154,718 candidates, pinpointing CaMnO3 as the most effective one among the screened candidates. …”
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A scoping review on metrics to quantify reproducibility: a multitude of questions leads to a multitude of metrics by Rachel Heyard, Samuel Pawel, Joris Frese, Bernhard Voelkl, Hanno Würbel, Sarah McCann, Leonhard Held, Kimberley E. Wever, Helena Hartmann, Louise Townsin, Stephanie Zellers

“…The metrics were characterized based on type (formulas and/or statistical models, frameworks, graphical representations, studies and questionnaires, algorithms), input required and appropriate application scenarios. …”
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Protecting kidney function: from mechanisms to therapeutic targets and traditional Chinese medicine by Yilin Meng, Lu Sui, Ligeer Che, Zihang Jin, Yutong Ma, Li Sun

“…Adaptive design and using human kidney organoid models for drug screening can determine the active ingredients efficiently. …”
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Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning by Jingjing Pan, Tao Guo, Haobo Kong, Wei Bu, Min Shao, Zhi Geng

“…Five machine learning algorithms were used to build predictive models. Models were evaluated through nested cross-validation to select the best one. …”
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Advancing clinical biochemistry: addressing gaps and driving future innovations by Haiou Cao, Enwa Felix Oghenemaro, Amaliya Latypova, Amaliya Latypova, Munthar Kadhim Abosaoda, Munthar Kadhim Abosaoda, Munthar Kadhim Abosaoda, Gaffar Sarwar Zaman, Anita Devi

“…However, concerns regarding algorithmic bias, data privacy, lack of transparency in decision-making (“black box” models), and over-reliance on automated systems pose significant challenges that must be addressed for responsible AI integration. …”
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Systematic elucidation of the effective constituents and potential mechanisms of Scrophulariae Radix against neoplasm based on LC-MS, network pharmacology, and molecular docking ap... by Shu-jie Yu, Xiao-bin Kong, Xin Jin, Meng-yi Shan, Gang Cheng, Pei-lu Wang, Wen-long Li, Pei-yuan Zhao, Yun-jie Sheng, Bing-qian He, Qi Shi, Hua-qiang Li, Qi-ming Zhao, Lu-ping Qin, Lu-ping Qin, Xiong-yu Meng, Xiong-yu Meng

“…As a result, the material–liquid ratio was significantly reduced from 100 g/mL to 32 g/mL, and the extraction efficiency was 1.332%, which was close to the predicted value of 1.346% in the response surface method, indicating that the algorithm model had a good fit. Next, a total of 738 compounds, including 161 terpenoids, 144 phenolic acids, 51 alkaloids, 24 flavonoids, 34 saccharides, 32 lignans and coumarins, 45 amino acids and derivatives, 23 organic acids, 134 lipids, 22 nucleotides and derivatives, and 59 other ingredients, were characterized from Scrophulariae Radix based on the accurate precursor and product ions, retention time, standards, fragmentation patterns, and previous publications. …”
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