Clinical characteristics and mortality of patients with heart failure in Southern Sweden from 2013 to 2019: a population-based cohort study by Awais Ashfaq, Madlaina Costa-Scharplatz, Björn Agvall, Jason Davidge, Kristina Malene Ødegaard, Mattias Olsson

“…Objectives To describe clinical characteristics and prognosis related to heart failure (HF) phenotypes in a community-based population by applying a novel algorithm to obtain ejection fractions (EF) from electronic medical records.Design Retrospective population-based cohort study.Setting Data were collected for all patients with HF in Southwest Sweden. …”
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A simple pedotransfer function to estimate fine fraction organic carbon contents of surface horizons in French soils by Eva Rabot, Pierre Barré, Claire Chenu, Amicie A. Delahaie, Manuel P. Martin, José-Luis Munera-Echeverri, Nicolas P.A. Saby

“…., fine fraction organic carbon (OCfine) and coarse fraction organic carbon, to improve our ability to understand controlling factors and predict SOC contents and SOC stability. …”
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Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis by Erfan Shirmohamadi, Reza Hosseini Dolama, Narjes Mohammadzadeh, Navid Ebrahimi, Negar Ghasemloo

“…Studies were included if they utilized machine learning algorithms, including HPI, to predict or detect IOH in adult surgical patients. …”
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Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

“…Developing robust, generalizable AI models and integrating multimodal imaging data promise to enhance diagnostic and prognostic capabilities in TCD and ultrasound. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…This study aims to address the critical lack of standardized guidelines for unmanned aerial vehicle (UAV) image acquisition strategies utilizing structure-from-motion (SfM) by focusing on 3D building exterior modeling. A comprehensive experimental analysis was conducted to systematically investigate and quantitatively evaluate the effects of various shooting patterns and parameters on SfM reconstruction quality and processing efficiency. …”
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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…Linear discriminant analysis was the most accurate (74.6%) algorithm with the shortest training time (0.9 s). …”
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What is the impact of longer patient travel distances and times on perioperative outcomes following revision knee replacement: a retrospective observational study using data for En... by Sarah Lamb, Tim Briggs, Andrew James Price, William Gray, Andrew D Toms, Jonathan Peter Evans, Jonathan Thomas Evans, Alexander Handel Matthews

“…Evolving practice in England aims to manage these patients in specialised centres with the intention of improving outcomes. This practice will result in longer travel distances and times in this frailer group of patients. …”
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Spironolactone Reduces the Risk of Death in Veterans With Heart Failure With Preserved Ejection Fraction by Katherine E. Kurgansky, Rachel Parker, Luc Djousse, David R. Gagnon, Jacob Joseph

“…Results from explanatory clinical trials suggest that spironolactone may help to improve outcomes in patients with HFpEF. We sought to investigate the effectiveness of spironolactone in reducing death and hospitalization outcomes for patients with HFpEF in a real‐world setting. …”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

“…This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches.…”
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Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques by Yashashree Mahale, Shrikrishna Kolhar, Anjali S. More

“…Six machine learning models, including logistic regression, support vector machine, decision tree, and random forest, along with gradient boosting algorithms using extreme gradient boost (XGBoost) and light gradient boosting machine frameworks, were implemented. …”
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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

“…Logistic regression analysis was used for feature selection to identify AKI predictors, and an extreme gradient boost (XGBoost) model was applied to all variables related to AKI events. …”
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Artificial Intelligence (AI) and Drug-Induced and Idiosyncratic Cytopenia: The Role of AI in Prevention, Prediction, and Patient Participation by Emmanuel Andrès, Amir El Hassani Hajjam, Frédéric Maloisel, Maria Belén Alonso-Ortiz, Manuel Méndez-Bailón, Thierry Lavigne, Xavier Jannot, Noel Lorenzo-Villalba

“…With its ability to process vast amounts of clinical, genomic, and pharmacovigilance data, AI can identify patterns and risk factors that may be missed by traditional methods. Machine learning algorithms can refine predictive models, enabling earlier detection and more accurate risk assessments. …”
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The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“… Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing…”
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Spatiotemporal Dynamics of Urban Green Spaces and Climatic Vulnerability of Togolese Cities in the Context of Rapid Urbanisation: The Case of Lome and Kara by Yetondé Deton, Hodabalo Kamou, Abalo Atato, Bimare Kombate, Abalo Mabafei, Josef Yoka, Marra Dourma, Atsu Kudzo Guelly, Komlan Batawila, Koffi Akpagana

“…Additionally, vulnerability models for 2022, 2060, and 2100 were developed using Shared Socioeconomic Pathways (SSP 2.45 and SSP 5.85) and a multifactorial modelling approach. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The advanced metaheuristic algorithms are a good addition to the literature, they are still in emerging stages and their performance can further be improved. …”
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A genetic association study of serum acute-phase C-reactive protein levels in rheumatoid arthritis: implications for clinical interpretation. by Benjamin Rhodes, Marilyn E Merriman, Andrew Harrison, Michael J Nissen, Malcolm Smith, Lisa Stamp, Sophia Steer, Tony R Merriman, Timothy J Vyse

“…The accuracy and utility of these algorithms might be improved by using a genetically adjusted CRP measurement.…”
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Some Aspects of Modern Distance Learning Technologies in the Field of Fire Safety by V. V. Volodchenkova, N. V. Peregudova, D. N. Kurkin, O. V. Chirko

“…The methodological basis of the research includes methods of theoretical research (analysis, synthesis, generalization, modeling), graphic and comparative method.Results. …”
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THE USE OF INTERACTIVE STUDYING METHODS IN TEACHING OPERATIVE SURGERY AND TOPOGRAPHIC ANATOMY by V.M. Fedorak

“… One of the main requirements of credit-modular system of studying at medical schools is improving the quality of training of future doctors, because patients' lives depend on their knowledge and skills. …”
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Mapping previously undetected trees reveals overlooked changes in pan-tropical tree cover by Shidong Liu, Jie Zhang, Li Wang, Philippe Ciais, Jianjun Zhang, Josep Penuelas, Biswajit Nath, Iskid Jacquet, Xia Wu, Shengping Ding, Wang Li, Ni Huang, Wanjuan Song, WenJian Ni, Zheng Niu

“…Fine-scale mapping can improve biogeochemical cycles modeling and vegetation-climate interactions, improving global change understanding.…”
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Development and validation of a nomogram for predicting in-hospital mortality in older adult hip fracture patients with atrial fibrillation: a retrospective study by Zhenli Li, Jing He, Tiezhu Yao, Guang Liu, Jing Liu, Ling Guo, Mengjia Li, Mengjia Li, Zhengkun Guan, Zhengkun Guan, Ruolian Gao, Jingtao Ma

“…Logistic regression (LR) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were employed to screen features. We further used Extreme Gradient Boosting (XGBoost) based on features selected by LR and LASSO algorithms to assist in identifying the final model-established features. …”
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