Improving aboveground biomass estimation by integrating ICESat-2 LiDAR sampling and tree species stratification strategies using multi-source datasets by Pan Liu, Chunying Ren, Zongming Wang, Mingming Jia

“…The AGB estimates exhibited a south-north gradient in all models, while UTSS performed best in both the low and high values. …”
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Appropriateness of NHS 111 Wales outcomes—using the Call Prioritisation Streaming System: a RAND/UCLA modified Delphi method by Craig Brown, Conrad Fivaz, Rebecca Malin, Mike Brady, Rhiannon Elizabeth Roynon, Peter Noblett

“…It achieves this by integrating individual patient data with a comprehensive computerised knowledge base, employing advanced software algorithms to produce recommendations and dispositions.Objectives While CPSS offers many advantages, its introduction marked a major shift in clinical digital processes. …”
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Practical applications of methods to incorporate patient preferences into medical decision models: a scoping review by Jakub Fusiak, Kousha Sarpari, Inger Ma, Ulrich Mansmann, Verena S. Hoffmann

“…Abstract Background Algorithms and models increasingly support clinical and shared decision-making. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. …”
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Hidden diversity in anthropophilic sand flies of the Monticola Series (Diptera, Psychodidae) by Bruno Leite Rodrigues, Alessandra Gutierrez de Oliveira, Leonardo Estevam Honorato da Silva, Thiago Vasconcelos dos Santos, Lidiane de Nazaré Carvalho de Oliveira, Felipe Dutra Rêgo, Andrey José de Andrade, Glédson Bandeira Maia, Israel de Souza Pinto, José Dilermando Andrade Filho, Eunice Aparecida Bianchi Galati

“…Species-delimitation algorithms split our dataset into at least three putative species for each taxon. …”
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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

“…In conclusion, the study highlights the promising role of AI in gastrointestinal endoscopy while underscoring the importance of continued research, algorithmic refinement, and the establishment of regulatory frameworks to fully harness its clinical potential. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…IntroductionThe state monitoring of tobacco leaves during the curing process is crucial for process control and automation of tobacco agricultural production. While most of the existing research on tobacco leaves state recognition focused on the temporal state of the leaves, the morphological state was often neglected. …”
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Strategies to Reduce Left Anterior Descending Artery and Left Ventricle Organ Doses in Radiotherapy Planning for Left-Sided Breast Cancer by Umut Diremsizoglu, Nezihan Topal, Aykut Oguz Konuk, Ibrahim Halil Suyusal, Dogacan Genc, Onur Ari, Hasan Furkan Cevik, Aysegul Ucuncu Kefeli, Maksut Gorkem Aksu, Emine Binnaz Sarper

“…The doses to the LAD and LV were added to the optimization algorithms. Two volumetric modulated arc therapy (VMAT) plans were created for each patient. …”
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Critical review of patient outcome study in head and neck cancer radiotherapy by Jingyuan Chen, Yunze Yang, Chenbin Liu, Hongying Feng, Jason M. Holmes, Lian Zhang, Steven J. Frank, Charles B. Simone, II, Daniel J. Ma, Samir H. Patel, Wei Liu

“…Three transformative methodological advances are reviewed: radiomics, AI-based algorithms, and causal inference frameworks. The integration of linear energy transfer in patient outcomes study, which has uncovered critical mechanisms behind unexpected toxicity, was also introduced for proton therapy. …”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…This study proposes an effective data-driven approach that utilizes machine learning algorithms to forecast reservoir pore pressure. A total of five machine learning algorithms, namely multivariable regression (MVR), polynomial regression (PR), random forest (RF), CatBoost regression, and multilayer perception (MLP), are applied in this research. …”
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Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks by Adoración Antolí, Adoración Antolí, Francisco Javier Rodriguez-Lozano, José Juan Cañas, Julia Vacas, Julia Vacas, Fátima Cuadrado, Fátima Cuadrado, Araceli Sánchez-Raya, Araceli Sánchez-Raya, Carolina Pérez-Dueñas, Carolina Pérez-Dueñas, Juan Carlos Gámez-Granados

“…The most informative areas of interest were those broadly grouping social and non-social stimuli, while more specific variables did not improve classification accuracy. …”
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Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Aims: The purpose of this study is to examine the current uses of AI in the early diagnosis, treatment, and detection of glaucoma while highlighting the advantages and drawbacks of different AI models and algorithms. …”
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The incremental value of tuberculosis detecting African giant pouched rats over Smear microscopy and Xpert MTB/RIF for Tanzanian TB detection. by Tefera B Agizew, Joseph Soka, Stephen Mwimanzi, Cynthia D Fast, Gilbert Mwesiga, Nashon Edward, Marygiven Stephen, Rehema Kondo, Christophe Cox, Negussie Beyene

“…Sputum-smear microscopy (smear) is being replaced by Xpert MTB/RIF (Xpert)-based diagnostic algorithms in many countries. We evaluated the incremental values of rat-based case detection over smear and Xpert.…”
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Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis by Hamed Hajishah, Danial Kazemi, Ehsan Safaee, Mohammad Javad Amini, Maral Peisepar, Mohammad Mahdi Tanhapour, Arian Tavasol

“…In total, 346 machine learning models were evaluated, with the most common algorithms being random forest, logistic regression, and gradient boosting. …”
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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…Our evaluation also shows that compared with two popular HD algorithms, the singlepass StrideHD model achieves a 27.6<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> and 8.2<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> reduction in inference memory cost without hurting the classification accuracy, while the iterative mode further provides 8.7<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> memory efficiency. …”
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Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis by Ji Hui Fan, Xiao Min Li

“…Background Circular RNAs (circRNAs) have been shown to play critical roles in the initiation and progression of chronic glomerulonephritis (CGN), while their role from mesangial cells in contributing to the pathogenesis of CGN is rarely understood. …”
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Explainable machine learning model and nomogram for predicting the efficacy of Traditional Chinese Medicine in treating Long COVID: a retrospective study by Jisheng Zhang, Yang Chen, Aijun Zhang, Yi Yang, Liqian Ma, Hangqi Meng, Jintao Wu, Kean Zhu, Jiangsong Zhang, Ke Lin, Xianming Lin

“…Data from 1,204 patients served as the training set, while 127 patients formed the testing set.ResultsWe employed five ML algorithms: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Neural Network (NN). …”
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A Comprehensive Review on Lithium-Ion Battery Lifetime Prediction and Aging Mechanism Analysis by Seyed Saeed Madani, Yasmin Shabeer, François Allard, Michael Fowler, Carlos Ziebert, Zuolu Wang, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou, Khay See, Kaveh Khalilpour

“…Lithium-ion batteries experience degradation with each cycle, and while aging-related deterioration cannot be entirely prevented, understanding its underlying mechanisms is crucial to slowing it down. …”
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The influence of pH and temperature on benthic chlorophyll-a: Insights from SHAP-XGBoost and random forest models by Sangar Khan, Noël P.D. Juvigny-Khenafou, Tatenda Dalu, Paul J. Milham, Yasir Hamid, Kamel Mohamed Eltohamy, Habib Ullah, Bahman Jabbarian Amiri, Hao Chen, Naicheng Wu

“…The SVR demonstrated that AT is vital for the upper and middle catchment reaches, while pH is more important in the lower reaches. …”
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DISPEL: A Python Framework for Developing Measures From Digital Health Technologies by A. Scotland, G. Cosne, A. Juraver, A. Karatsidis, J. Penalver-Andres, E. Bartholome, C. M. Kanzler, C. Mazza, D. Roggen, C. Hinchliffe, S. Del Din, S. Belachew

“…<italic>Conclusion</italic>: DISPEL supports SDM development for clinical trials by providing a production-grade Python framework and a large set of already implemented SDMs. While the framework has already been refined based on clinical trials&#x2019; data, ad-hoc validation of the provided algorithms in their specific context of use is recommended to the users.…”
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