Towards a Digital Twin for Gas Turbines: Thermodynamic Modeling, Critical Parameter Estimation, and Performance Optimization Using PINN and PSO by Jian Tiong Lim, Achnaf Habibullah, Eddie Yin Kwee Ng

“…Ultimately, the proposed methods aim to enhance GT operations via a data-driven digital twin concept combination of deep learning and optimization algorithms.…”
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Abnormal heart sound recognition using SVM and LSTM models in real-time mode by Moy’awiah A. Al-Shannaq, Areen Nasrawi, Abed Al-Raouf K. Bsoul, Ahmad A. Saifan

“…Normal heart sounds have a special rhythmic pattern as an indicator of heart integrity. Many experts concentrate on diagnosing the heart by automatic digital auscultation systems which find various distinguishable characteristics for heart sound classifications. …”
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From Simulation to Field Validation: A Digital Twin-Driven Sim2real Transfer Approach for Strawberry Fruit Detection and Sizing by Omeed Mirbod, Daeun Choi, John K. Schueller

“…Traditional simulators often lack visual realism, leading many studies to mix real images or adopt domain adaptation methods to address the reality gap. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…Text processing has been the latest trend in research, with many machine learning and deep learning techniques widely used for it. …”
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Improved Soybean Mapping with Spectral Gaussian Mixture Modeling by Guilong Xiao, Kaiqi Du, Shuangxi Miao, Xuecao Li, Anne Gobin, Tiecheng Bai, Miao Zhang, Bingfang Wu, Jianxi Huang

“…However, traditional sample-driven soybean mapping algorithms often rely on extensive, representative datasets, which can limit their applicability across different regions and periods. …”
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Predicting ICU mortality in heart failure patients based on blood tests and vital signs by Yeao Wang, Jianke Rong, Zhili Wei, Xiaoyu Bai, YunDan Deng

“…Critically ill patients are often unsuitable for extensive diagnostic tests, and many primary care hospitals lack comprehensive diagnostic equipment. …”
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Treatment of infections in young infants in low- and middle-income countries: a systematic review and meta-analysis of frontline health worker diagnosis and antibiotic access. by Anne C C Lee, Aruna Chandran, Hadley K Herbert, Naoko Kozuki, Perry Markell, Rashed Shah, Harry Campbell, Igor Rudan, Abdullah H Baqui

“…For study question 1, meta-analysis showed that clinical sign-based algorithms predicted bacterial infection in young infants with high sensitivity (87%, 95% CI 82%-91%) and lower specificity (62%, 95% CI 48%-75%) (six studies, n = 14,254). …”
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Design, Development and Implementation of iALERTS (Informatics Analytics for Long-term Evaluation and Repercussions Tracking of SARS-CoV-2 Infection): A Research Protocol by Krishna Mohan Surapaneni, Manmohan Singhal, Ashish Joshi

“…This platform employs machine learning algorithms to predict the likelihood of PASC development among Coronavirus Disease-19 (COVID-19) survivors. …”
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Economic burden of the novel coronavirus infection: a systematic review by V. M. Timiryanova, I. A. Lakman, N. Sh. Zagidullin, D. F. Gareeva

“…Predominantly, the estimates involve the calculation of quality-adjusted life years lost (QALY) (66.3%), 37.6% of the studies are based on the results of constructing scenario models, 28.8% consume algorithms of epidemiological SIR (susceptible, infected, or recovered) models, and 66.3% provide for cost assessment. …”
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Implementasi Metode Backpropogation dengan Inisialisasi Bobot Nguyen Widrow untuk Peramalan Harga Saham by Eliv Kurniawan, Hari Wibawanto, Djoko Adi Widodo

“…One of the weight initialization algorithms that can be increase the execution time is nguyen-widrow. …”
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Semantic influence of programming on the development of thinking of students: background, research and prospects by M. U. Mukasheva, Y. V. Payevskaya

“…Papert), elements of the theory of computation, theory of algorithms and programming (D. Fink, D. Knut, N. Wirth and others).The empirical data on the study of the semantic influence of programming on the development of mental abilities of primary school students in the process of learning programming (Scratch) were obtained using a specially developed technique (framework) for studying the dynamics of the development of computational thinking. …”
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Growth dynamics of splenic artery aneurysms: morphology, comorbidities, and vascular anatomical factors by Ahmet Tanyeri, Aygün Katmerlikaya, Rıdvan Akbulut, Mehmet Burak Çildağ

“…Abstract Background Splenic artery aneurysms (SAAs) are the most common visceral artery aneurysms, often detected incidentally due to the widespread use of cross-sectional imaging. While many remain asymptomatic, rupture carries a high mortality risk. …”
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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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Stochastic Variance Reduced Primal–Dual Hybrid Gradient Methods for Saddle-Point Problems by Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu

“…Recently, many stochastic Alternating Direction Methods of Multipliers (ADMMs) have been proposed to solve large-scale machine learning problems. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…Artificial intelligence algorithms are primarily divided into methods based on group optimization problems and machine learning algorithms. …”
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Glucagon-like peptide-1 receptor agonist use prior to spinal surgery results in reduced postoperative length of stay: A propensity-score matched analysis by Samuel N. Goldman, BS, Kyle Mani, BE, Thomas Scharfenberger, BS, Emily Kleinbart, BA, Aaron T. Hui, BS, Rafael De la Garza Ramos, MD, Mitchell S. Fourman, MD, MPhil, Ananth S. Eleswarapu, MD

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Opportunities and challenges of quantum computing for climate modeling by Mierk Schwabe, Lorenzo Pastori, Inés de Vega, Pierre Gentine, Luigi Iapichino, Valtteri Lahtinen, Martin Leib, Jeanette Miriam Lorenz, Veronika Eyring

“…We discuss how quantum computers could accelerate climate models by solving the underlying differential equations faster, how quantum machine learning could better represent subgrid-scale phenomena in ESMs even with currently available noisy intermediate-scale quantum devices, how quantum algorithms aimed at solving optimization problems could assist in tuning the many parameters in ESMs, a currently time-consuming and challenging process, and how quantum computers could aid in the analysis of climate models. …”
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Using artificial intelligence and promoter-level transcriptome analysis to identify a biomarker as a possible prognostic predictor of cardiac complications in male patients with Fa... by Hiroshi Kobayashi, Norio Nakata, Sayoko Izuka, Kenichi Hongo, Masako Nishikawa

“…To predict cardiac complications of Fabry disease, we extracted RNA from the venous blood of patients for cap analysis of gene expression (CAGE), performed likelihood ratio tests for each RNA expression dataset obtained from individuals with and without cardiac complications, and analyzed the correlation between cardiac functional factors observed using magnetic resonance imaging data extracted using artificial intelligence algorithms and RNA expression. Our findings showed that CHN1 expression was significantly higher in male Fabry disease patients with cardiac complications and that it could be associated with many cardiac functional factors. …”
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Artificial Intelligence in Healthcare: Medical Students' Perspectives on Balancing Innovation, Ethics, and Patient-Centered Care by Eleanor Roy, Sara Malafa, Lina M. Adwer, Houda Tabache, Tanishqa Sheth, Vasudha Mishra, Moaz Elsayed Abouelmagd, Andrea Cushieri, Sajjad Ahmed Khan, Mihnea-Alexandru Gaman, Juan C. Puyana, Francisco Javier Bonilla-Escobar

“…We argue that while AI can support autonomy by providing personalized insights, opaque “black box” models and lack of informed consent can undermine shared decision-making and trust. Algorithmic bias further threatens equity in care, as many AI systems are trained on unrepresentative datasets, leading to disparities in diagnosis and treatment. …”
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Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose by Scott D. Emerson, Taylor McLinden, Paul Sereda, Amanda M. Yonkman, Jason Trigg, Sandra Peterson, Robert S. Hogg, Kate A. Salters, Viviane D. Lima, Rolando Barrios

“…Key considerations were organized around four themes: 1) Know the data and their primary use (understand their scope and limitations); 2) Understand classification and coding systems (appreciate the nuances regarding classification systems, versions, how they are employed in the primary uses of the data, and querying the values); 3) Transform data into meaningful forms (process data and apply identification algorithms, when necessary); 4) Recognize the importance of validity when defining analytic variables (make meaningful inferences based on data/algorithms). …”
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