Aerosol layer height (ALH) retrievals from oxygen absorption bands: intercomparison and validation among different satellite platforms, GEMS, EPIC, and TROPOMI by H. Kim, H. Kim, X. Chen, X. Chen, J. Wang, J. Wang, J. Wang, J. Wang, Z. Lu, Z. Lu, Z. Lu, M. Zhou, G. R. Carmichael, G. R. Carmichael, S. S. Park, J. Kim

“…The differences due to the inconsistent definitions of ALH in various retrieval algorithms are investigated and eliminated before comparison. …”
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Incidence and Predictors of Acute Kidney Injury Following Advanced Ovarian Cancer Cytoreduction at a Tertiary UK Centre: An Exploratory Analysis and Insights from Explainable Artif... by Elizabeth Ratcliffe, Ciara Devlin, Sarika Munot, Timothy Broadhead, Amudha Thangavelu, Michela Quaranta, David Nugent, Evangelos Kalampokis, Diederick De Jong, Alexandros Laios

“…Mortality rates were similar between patients with and without AKI. AI-driven algorithms highlighted the complexity of AKI prediction and provided individual risk profiles, enabling future stratification and prompting different frequencies of AKI monitoring following cytoreduction. …”
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Effects of Exchange, Anisotropic, and External Field Couplings on a Nanoscale Spin-2 and Spin-3/2 System: A Thermomagnetic Analysis by Julio Cesar Madera, Elisabeth Restrepo-Parra, Nicolás De La Espriella

“…To determine the thermomagnetic behaviors of the nanoparticle, numerical simulations using Monte Carlo techniques and thermal bath class algorithms are performed. The results exhibit the effects of exchange couplings (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>J</mi><mn>1</mn></msub><mo>,</mo><msubsup><mi>J</mi><mn>2</mn><mo>′</mo></msubsup></mrow></semantics></math></inline-formula>), magnetocrystalline anisotropies (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>D</mi><mrow><mn>3</mn><mo>/</mo><mn>2</mn></mrow><mo>′</mo></msubsup><mo>,</mo><msubsup><mi>D</mi><mn>2</mn><mo>′</mo></msubsup></mrow></semantics></math></inline-formula>), and external magnetic fields (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>h</mi><mo>′</mo></msup></semantics></math></inline-formula>) on the finite-temperature phase diagrams of magnetization (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mi>T</mi></msub></semantics></math></inline-formula>), magnetic susceptibility (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>χ</mi><mi>T</mi></msub></semantics></math></inline-formula>), and thermal energy (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>B</mi></msub><msup><mi>T</mi><mo>′</mo></msup></mrow></semantics></math></inline-formula>). …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…As many as 12 machine learning (ML) algorithms, namely, logistic regression (LR), decision tree (DT), random forest (RF), gradient boosting (GB), AdaBoost, XGBoost, Naive Bayes (NB), support vector machine (SVM), light gradient-boosting machine (LightGBM), K-nearest neighbors (KNN), extremely randomized trees (ET), and voting classifier (VC), were performed. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…The machine learning algorithms employed in this study includes logistic regression (LR), decision tree (DT), random forest (RF), extreme gradient boosting machine (eXGBM), neural network (NN), and k-nearest neighbor (KNN). …”
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Subsurface cavity detection in a karst environment using electrical resistivity (er): a case study from yongweol-ri, South Korea by Farooq Muhammad, et al

“…The resistivity data was inverted using 2D and 3D algorithms based on the least squares smoothness constraint technique. …”
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An Efficient Analytical Method for Determining the Effects of Silver Nanoparticles on Vibrio parahaemolyticus in Estuarine Water by Xiangyi HOU, Xiaoyang WANG, Yuanyuan ZHANG, Ruohan LIANG, Feng LU, Qianqian YANG, Xiaodan PU, Yan ZHANG, Keming QU, Xuzhi ZHANG

“…Based on a 32-channel C4 detector and special algorithms, we developed a 32-channel electronic microbial growth analyzer (EMGA). …”
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Autoconcepto físico en estudiantes universitarios: Generación de perfiles por clasificación jerárquica sobre componentes principales (Physical self-concept in university students:... by Luis Alberto Cardozo, Jhonatan C. Peña-Ibagón, Widad Florez-Escobar, Carlos A. Castillo-Daza, Diego A. Bonilla-Ocampo, Javier L. Reina-Monroy

“…The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…The qSepsis was derived by three ML algorithms, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). …”
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Providing a Framework for Assessing and Evaluating Network Data Studies in the Fight Against Social Anomalies by Mohammad Khalili, Hamzehali Nourmohammadi, Nader Naghshineh

“…Additionally, clustering techniques, such as k-means, were employed to identify different forms of theft crimes. Classification algorithms, including neural networks, Bayesian rules, Bayesian navigation, and support vector machines, were used to predict theft crimes. …”
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Study protocol for a pragmatic randomised controlled trial in Belgian primary care and hospital settings on the effectiveness of an eHealth self-management support programme consis... by Josefien van Olmen, An De Groef, Nele Devoogdt, Lore Dams, Bart Morlion, Mira Meeus, G Lorimer Moseley, Louise K Wiles, Peter Hibbert, Patrick Neven, Ines Nevelsteen, Steffen Fieuws, Geert Crombez, Michel Mertens, Ceren Gursen, Wiebren Tjalma, Lander Willem, Lauren C Heathcote, Mark Catley, Anna Vogelzang, Marthe Van Overbeke, Emma Tack, Sophie Van Dijck, Annick L De Paepe, Rani Vanhoudt, Davina Wildemeersch, Femke De Backere

“…Utilising a chatbot format, the eHealth programme delivers pain science education and promotes physical activity (PA), personalised through decision-tree-based algorithms to support pain self-management. The programme aims to empower patients with understanding, coping skills and self-management techniques to reduce pain-related disability and enhance participation in daily life. …”
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Research Status and Prospects of Key Technologies for Rice Smart Unmanned Farms by YU Fenghua, XU Tongyu, GUO Zhonghui, BAI Juchi, XIANG Shuang, GUO Sien, JIN Zhongyu, LI Shilong, WANG Shikuan, LIU Meihan, HUI Yinxuan

“…Rice yield estimation technology is mainly used to predict yield by combining multi-source data and algorithms, but there are still problems such as the difficulty of integrating multi-source data, which requires further research. …”
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Integrating Gut Microbiome and Metabolomics with Magnetic Resonance Enterography to Advance Bowel Damage Prediction in Crohn&amp;rsquo;s Disease by Huang L, Meng J, Lin S, Peng Z, Zhang R, Shen X, Zheng W, Zheng Q, Wu L, Wang X, Wang Y, Mao R, Sun C, Li X, Feng ST

“…Seven machine learning algorithms, each paired with seven distinct combinations of multi-omics features, were evaluated using nested 5-fold cross-validation to construct an optimal prediction model. …”
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Flow Characteristics by Blood Speckle Imaging in Non-Stenotic Congenital Aortic Root Disease Surrounding Valve-Preserving Operations by Shihao Liu, Justin T. Tretter, Lama Dakik, Hani K. Najm, Debkalpa Goswami, Jennifer K. Ryan, Elias Sundström

“…BSI, utilizing block-matching algorithms, enabled detailed visualization and quantification of flow parameters from the echocardiographic data. …”
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Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Generative AI in Medical Writing Generative AI tools or “chatbots” combine the adaptive learning capabilities of deep learning algorithms and natural language processing, resulting in a virtual assistant or aide that is capable of answering queries, following commands, and improving its responses according to the vast data available on the Internet in addition to user responses.3 This has allowed the accomplishment of various complex tasks within seconds that would otherwise require hours of trial and error. …”
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Un outil éthique, automatisé et totalement autonome pour étudier la cognition chez les primates by Jonas Fizet, Adam Rimele, Thierry Pebayle, Jean Christophe Cassel, Christian Kelche, Helene Meunier

“…Une particularité du programme que nous avons développé est l’implémentation d’un nouveau processus d’apprentissage totalement informatisé et autonome, ne nécessitant aucune intervention de l’expérimentateur tout au long de l’étude. Basé sur des algorithmes intelligents, ce dernier permet une variation en temps réel de la difficulté des tâches en fonction de l’évolution des performances individuelles. …”
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Digital Watermarking Based on Contourlet-SVD by Seyedeh Akram Hosseini, Sedigheh Ghofrani

“…The proposed scheme is based on embedding watermark bits into the singular value of the selected blocks within low-pass sub-band of the original gray image CT. Two algorithms, the first uses adaptive quantization and the second uses quantization step, are implemented. …”
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A Machine Learning Model for Predicting Breast Cancer Recurrence and Supporting Personalized Treatment Decisions Through Comprehensive Feature Selection and Explainable Ensemble Le... by Lee TF, Shiau JP, Chen CH, Yun WP, Wuu CS, Huang YJ, Yeh SA, Chen HC, Chao PJ

“…An ensemble learning model was developed based on multiple machine learning algorithms, with SHAP (Shapley additive explanations) used for interpretability.Results: The ensemble model achieved an AUC of 0.817, outperforming the best single model (AUC 0.711), demonstrating improved predictive accuracy and stability. …”
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Interplay between tumor mutation burden and the tumor microenvironment predicts the prognosis of pan-cancer anti-PD-1/PD-L1 therapy by Wuyuan Liao, Wuyuan Liao, Wuyuan Liao, Xinwei Zhou, Xinwei Zhou, Hansen Lin, Hansen Lin, Zihao Feng, Zihao Feng, Xinyan Chen, Yuhang Chen, Yuhang Chen, Minyu Chen, Minyu Chen, Mingjie Lin, Mingjie Lin, Gaosheng Yao, Gaosheng Yao, Jinwei Chen, Jinwei Chen, Haoqian Feng, Haoqian Feng, Yinghan Wang, Yinghan Wang, Zhiping Tan, Zhiping Tan, Youyan Tan, Jun Lu, Jun Lu, Pengju Li, Pengju Li, Jinhuan Wei, Jinhuan Wei, Li Luo, Li Luo, Liangmin Fu, Liangmin Fu, Liangmin Fu

“…Additionally, we employed algorithms such as CIBERSORT and ESTIMATE to assess the correlation between the risk score and TME components. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…In this challenging context, innovative algorithms and model designs are crucial for addressing differences in CSI features between various actions and enhancing the model’s generalization ability and robustness.Method This study explores human actions’ physical and MIMO transmission characteristics, proposing a deep learning-based human action recognition method that employs a dual attention mechanism and a multi-channel, multi-scale fusion temporal convolution network to address the above challenges. …”
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