Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…This study proposes an improved method based on multi-source data, combining the Sentinel-2A spectral response function (SRF) and computer algorithms, to overcome the limitations of traditional methods. …”
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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…Large-scale, automated cross-sectional and longitudinal cerebral biomarker extraction from FLAIR datasets could progress disease characterization, improve disease monitoring, and help to determine optimal intervention times. …”
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The potential role of next-generation sequencing in identifying MET amplification and disclosing resistance mechanisms in NSCLC patients with osimertinib resistance by Xiao Xiao, Xiao Xiao, Ren Xu, Ren Xu, Jun Lu, Beibei Xin, Chenyang Wang, Kexin Zhu, Hao Zhang, Xinyu Chen

“…With FISH results as gold standard, enumeration algorithm was applied to establish the optimal model for identifying MET amplification using gene copy number (GCN) data.ResultsThe optimal model for identifying MET amplification was constructed based on the GCN of MET, BRAF, CDK6 and CYP3A4, which achieved a 74.0% overall agreement with FISH and performed well in identifying MET amplification except polysomy with a sensitivity of 85.7% and a specificity of 93.9%. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…These findings demonstrate the potential of AI-driven diagnostic tools to identify high-risk patients, support optimized treatment strategies, and ultimately improve clinical implications.…”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…We hope to identify high-risk patients for early intervention to reduce the incidence of HF and improve their quality of life.…”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…Using the RF feature selection (FS) method to select optimal factors as model input variables improved simulation accuracy compared with using all factors or selecting based on Pearson correlation analysis (R² increased by 1.75%–64.71%). …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…Regarding model performance in SOC content prediction, GNN is more suitable for Model (i) and Model (iii), while CNN is more appropriate for Model (ii). In conclusion, ResoCroS-Net achieved collaborative optimization of spatial-spectral features across scales, provided a significant advantage in improving the accuracy of quantitative remote sensing, offers an efficient and accurate SOC monitoring tool, providing a practical basis for the integrated remote sensing theory of ‘ground-air-space’.…”
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Regularized Kaczmarz Solvers for Robust Inverse Laplace Transforms by Marta González-Lázaro, Eduardo Viciana, Víctor Valdivieso, Ignacio Fernández, Francisco Manuel Arrabal-Campos

“…Quantitative evaluation via mean squared error (MSE), Wasserstein distance, total variation, peak signal-to-noise ratio (PSNR), and runtime demonstrates that Wasserstein–Kaczmarz attains an optimal balance of speed (0.53 s per inversion) and accuracy (MSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.7</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>8</mn></mrow></msup></mrow></semantics></math></inline-formula>), while TRAIn achieves the highest fidelity (MSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1.5</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>8</mn></mrow></msup></mrow></semantics></math></inline-formula>) at a modest computational cost. …”
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Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning by Hui Xu, Xingwang Peng, Ziyu Peng, Rui Wang, Rui Zhou, Lianguo Fu

“…Second, ML models were constructed based on the logistic regression (LR), decision tree (DT), support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms, after which random sampling and tenfold cross-validation were separately used to evaluate and compare these models and identify the optimal model. …”
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UAV image analysis for detecting rice seedling gaps and gap effect on grain yield by Sanai Li, Yubin Yang, Jing Zhang, Lloyd T. (Ted) Wilson, Stanley Omar P.B. Samonte, Fugen Dou, Tanumoy Bera, Xin-Gen Zhou, Darlene Sanchez, Jing Wang

“…This study highlights the importance of monitoring seedling gaps to guide adaptive crop management, offering insights to optimize decisions on replanting or adjusting planting strategies to minimize gaps and improve yield.…”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…Background: With the introduction of sensing-enabled deep brain stimulation devices, characterization of long-term biomarker dynamics is of growing importance for treatment optimization. The microlesion effect is a well-known phenomenon of transient clinical improvement in the acute post-operative phase. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. …”
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Double‐row suture‐bridge technique does not yield better clinical and radiological results than single‐row technique in patients older than 55 years at 2 years minimum follow‐up: A... by Vito Gaetano Rinaldi, Sassoli Iacopo, Federico Coliva, Antongiulio Favero, Alberto Bazzocchi, Marco Miceli, Stefano Di Paolo, Stefano Zaffagnini, Giulio Maria Marcheggiani Muccioli

“…Further research, including randomized controlled trials with long‐term follow‐up, is needed to refine treatment algorithms and improve patient outcomes in rotator cuff surgery. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

“…In light of the ongoing global hunger crisis, it is imperative to improve food production in accordance with Sustainable Development Goal 2.0, which aims to eliminate hunger while promoting sustainable agricultural practices. …”
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Monolayer graphene/platinum-modified 3D origami microfluidic paper-based biosensor for smartphone-assisted biomarkers detection by Arda Fridua Putra, Annisa Septyana Ningrum, Suyanto Suyanto, Vania Mitha Pratiwi, Muhammad Yusuf Hakim Widianto, Irkham Irkham, Wulan Tri Wahyuni, Isnaini Rahmawati, Fu-Ming Wang, Chi-Hsien Huang, Ruri Agung Wahyuono

“…Conclusion: The 3D origami structure facilitates efficient fluid handling and multiplex detection, while the nanocatalyst modification improves pore infiltration and sensitivity. …”
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Research on Characteristics and Influencing Factors of High Temperature Disaster Risk in Wuhan Based on Local Climate Zone by Shujing GUO, Li ZHANG

“…Finally, high temperature service facilities should be improved to enhance the city's coping ability.…”
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Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

“…We evaluated the effectiveness of various supervised ML algorithms and identified the optimal configurations for these applications. …”
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Construction and application of a drought classification model for tea plantations based on multi-source remote sensing by Yang Xu, Yilin Mao, He Li, Xiaojiang Li, Litao Sun, Kai Fan, Zhipeng Li, Shuting Gong, Zhaotang Ding, Yu Wang

“…To address this gap, we propose RSDCM (Remote Sensing-based Drought Classification Model), an improved Genetic Algorithm-Backpropagation (GA-BP) combined with MS + TIR framework that optimizes initial weights and thresholds via GA's global search (hidden layer=1, neurons in the hidden layers=5, 50 generations, population size=5, NonUnifMutation operators) to escape local minima and accelerate convergence. …”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…The development of an intelligent system for processing semistructured data has improved the analysis of comments on videos in social networks through a combination of various machine learning models and algorithms. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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