Cardiovascular Disease Screening in Primary School Children by Alena Bagkaki, Fragiskos Parthenakis, Gregory Chlouverakis, Emmanouil Galanakis, Ioannis Germanakis

“…Following expert verification of responses and obtained data, assisted by designated electronic health record with incorporated decision support algorithms (phase II), pediatric cardiology evaluation at the tertiary referral center followed (phase III). …”
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Analisis Buku “Mari Belajar Matematika” Karya Dewi Nuharini dan Sulis Priyanto Tahun 2017 by Arum Weni, Ryky Mandar Sary, Veryliana Purnamasari

“…The results of the analysis that has been carried out are the percentage details for each indicator as follows. (1) Materials containing concepts, definitions, procedures/algorithms, theorems and properties get 75% percentage in the appropriate category. (2) The material contains examples and practice questions that support the concept of getting a percentage of 100% with a very appropriate category. (3) The material contains explanations that can build students' knowledge and gets a percentage of 100% with a very appropriate category. …”
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Dynamic analysis and optimal control of a hybrid fractional monkeypox disease model in terms of external factors by Saima Rashid, Abdul Bariq, Ilyas Ali, Sobia Sultana, Ayesha Siddiqa, Sayed K. Elagan

“…We remark that in various time scale domains $$\mathbb {N}_{\ell }$$ , the investigated discrete formulations will be $$\rho ^{2}$$ -nonincreasing or $$\rho ^{2}$$ -nondecreasing by examining $$\rho$$ -monotonicity formulations and the basic properties of the suggested operator. Algorithms are constructed in the discrete generalized Mittag–Leffler (GML) kernel for mathematical simulations, emphasizing the effects of the infection resulting from multiple factors. …”
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Picometre-level surface control of a closed-loop, adaptive X-ray mirror with integrated real-time interferometric feedback by Ioana-Theodora Nistea, Simon G. Alcock, Andrew Foster, Vivek Badami, Riccardo Signorato, Matteo Fusco

“…Aside from demonstrating the extreme sensitivity of the interferometer sensors, this study also highlights the voltage repeatability and stability of the programmable high-voltage power supply, the accuracy of the correction-calculation algorithms and the almost instantaneous response of the bimorph mirror to command voltage pulses. …”
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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study by Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao

“…Machine learning methods are flexible prediction algorithms with potential advantages over conventional regression. …”
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Evaluating pre-processing and deep learning methods in medical imaging: Combined effectiveness across multiple modalities by Thien B. Nguyen-Tat, Tran Quang Hung, Pham Tien Nam, Vuong M. Ngo

“…This study provides a thorough evaluation of the performance of different preprocessing methods and deep learning algorithms across commonly used medical imaging modalities. …”
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DIGITAL TOOLS FOR MATCHING QUALIFICATIONS TO THE LEVELS OF THE NATIONAL QUALIFICATIONS FRAMEWORK by Volodymyr Kovtunets, Sergiy Londar, Serhii Melnyk, Oles Kovtunets

“…The novelty of the article is that for the first time in national and international practice, it proposes an alternative/supplementary algorithmic method for determining the level of certain full and/or partial professional qualifications by the National Qualifications Framework, thus creating prerequisites for further automation of the activities of professional standards developers. …”
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Baseline [18F]FDG PET/CT radiomics for predicting interim efficacy in follicular lymphoma treated with first-line R-CHOP by Zeying Wen, Xiaohe Gao, Qingxia Wu, Jianwei Yang, Jian Sun, Keliu Wu, Hongfei Zhao, Ruihua Wang, Yanmei Li

“…Univariate analysis was employed to identify clinical risk factors, and correlation coefficients, MRMR, and LASSO algorithms were used for dimensionality reduction and selection of radiomics features. …”
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Comprehensive approach to predictive analysis and anomaly detection for road crash fatalities by Chopparapu Gowthami, S. Kavitha

“…The research offers policymakers, transportation authorities, and safety advocates practical insights by utilizing sophisticated machine-learning algorithms and integrating multiple datasets. Road crash fatalities can be decreased and safer transportation systems can be established by using the predictive models that have been created as a proactive tool for identifying high-risk regions and allocating resources for targeted improvements. …”
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In Silico Identification of New Anti-SARS-CoV-2 Main Protease (Mpro) Molecules with Pharmacokinetic Properties from Natural Sources Using Molecular Dynamics (MD) Simulations and Hi... by Harrison Onyango, Patrick Odhiambo, David Angwenyi, Patrick Okoth

“…In this study, computational algorithms were utilized for virtual screening of a library of natural compounds in the ZINC database for their affinity towards SARS-CoV-2 Mpro. …”
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Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy by Jun Peng, Wenqi Zhao, Lu Zhou, Kun Ding

“…In addition, key biomarkers were acquired by two machine learning algorithms, then immune infiltration analysis, Gene Set Enrichment Analysis (GSEA), and potential drugs screening were conducted. …”
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Evaluation of Real-World Evidence to Assess Effectiveness Outcomes of Janus Kinase Inhibitors for Rheumatoid Arthritis: A Systematic Review of US Studies by Gandy C, Bazzazzadehgan S, Bruera S, Huang Y

“…Six studies applied effectiveness algorithms, with 14.8– 26% of patients meeting effective treatment criteria. …”
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Analyzing the association of critical illness and cardioversion success in patients with atrial fibrillation at the emergency department by Sophie Gupta, Sebastian Schnaubelt, Julia Oppenauer, Martin Lutnik, Filippo Cacioppo, Alexander Spiel, Hans Domanovits, Patrick Sulzgruber, Jan Niederdöckl

“…Abstract In critically ill patients with atrial fibrillation (AF), standard treatment algorithms might not be applicable. Emergency departments (ED) play a crucial role in implementing individualized treatment approaches. …”
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Modern methods of visualization of the angle of the anterior chamber of the eye in the diagnosis and treatment of glaucoma by A.V. Sidorova, A.V. Starostina, K.A. Stefankova, E.S. Mustafaeva, M.S. Jereshtieva, Anna A. Aydinyan

“…Taking into account the variety of clinical forms of glaucoma and the insufficient equipment of medical institutions, especially primary care, it can be concluded that it is necessary to improve diagnostic algorithms. Methods such as electronic gonioscopy, optical coherence tomography of the eye anterior segment and ultrasound biomicroscopy will make the diagnostic process more accurate and informative, help to correctly diagnose and determine treatment tactics for both primary care physicians and surgeons. …”
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The systemic oxidative stress index predicts clinical outcomes of esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy by Jifeng Feng, Jifeng Feng, Liang Wang, Xun Yang, Qixun Chen, Qixun Chen

“…Then, a new staging that included TNM and SOSI based on RPA algorithms was produced. In terms of prognostication, the RPA model performed significantly better than TNM classification.ConclusionSOSI is a simple and useful score based on available SOS-related indices. …”
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Predictive Policing and Enhancing Security Performance through Artificial Intelligence Applications by Bensalem Kheira

“…The application of AI in predictive policing extends beyond pattern recognition. Advanced algorithms adapt to the dynamic nature of criminal activities, addressing evolving trends and innovative methodologies employed by offenders. …”
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Analytical performance of OncoPrism-HNSCC, an RNA-based assay to inform immune checkpoint inhibitor treatment decisions for recurrent/metastatic head and neck squamous cell carcino... by Jeffrey Hiken, Jon Earls, Kevin C. Flanagan, Rachel L. Wellinghoff, Michelle Ponder, David N. Messina, Jarret I. Glasscock, Eric J. Duncavage

“…The assay combines next generation RNA sequencing-based immunomodulatory gene expression signatures with machine learning algorithms to generate an OncoPrism score that classifies patients as having low, medium, or high likelihood of disease control in response to ICI treatment. …”
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Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar by Shiyu Xie, Tao Zhang, Siming You, Santanu Mukherjee, Mingjun Pu, Qing Chen, Yaosheng Wang, Esmat F. Ali, Hamada Abdelrahman, Jörg Rinklebe, Sang Soo Lee, Sabry M. Shaheen

“…Also, different ML algorithms were used to model and predict the hydrochar solid yield, properties, and nutrients content. …”
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Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). …”
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Recent Developments to the ANSWERS® Monte Carlo Codes MONK® and MCBEND® by Fildes Jessica, Richards Simon, Bird Adam, Cox Andrew, Fry Timothy, Hanlon David, Jones Brian, Long David, Tantillo Francesco, Wright George, Hiles Richard

“…The geometry capabilities have been enhanced by the addition of novel stochastic geometry algorithms for modelling highly disordered heterogeneous mixtures and random distributions of shapes. …”
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