A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images by Hassaan Haider Syed, Muhammad Attique Khan, Usman Tariq, Ammar Armghan, Fayadh Alenezi, Junaid Ali Khan, Seungmin Rho, Seifedine Kadry, Venkatesan Rajinikanth

“…The proposed method includes four core steps: (i) preparing a database of three different classes such as COVID-19, pneumonia, and normal; (ii) modifying three pretrained deep learning models such as VGG16, ResNet50, and ResNet101 for the classification of COVID-19-positive scans; (iii) proposing an activation function and improving the firefly algorithm for feature selection; and (iv) fusing optimal selected features using descending order serial approach and classifying using multiclass supervised learning algorithms. …”
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THE ROLE OF ORGANIZATIONAL AND ECONOMIC MECHANISM OF STRATEGIC COMPANY MANAGEMENT IN THE NATIONAL ECONOMY by О. Parfentieva, А. Grechan, A. Bezuglyi, К. Kompanets, О. Salimon

“…The mechanism of strategic company management based on investment activity is suggested. An algorithm for improving strategic investment management is suggested. …”
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Beam-steering of a single-element nano-antenna with two transferring dielectric flat lenses by Fatma E. Helmy, Ibrahim I. Ibrahim, Amany M. Saleh

“…Two inhomogeneous rectangular dielectric flat lenses modelled with different materials are used in the switched-beam nano-antenna (NA) to boost and steer radiation in a specific direction by shifting each lens. …”
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Application of Artificial Intelligence in Support of NAFLD Diagnosis by Jakub Płudowski, Jan Mulawka

“…The system consists of several modules: medical data aggregation, AI model training using advanced machine learning algorithms, Explainable AI generating reports, and patient diagnosis by ensemble model. …”
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Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa by Tafadzwa Dzinamarira, Elliot Mbunge, Claire Steiner, Enos Moyo, Adewale Akinjeji, Kaunda Yamba, Loveday Mwila, Claude Mambo Muvunyi

“…Effective policy development is equally essential to establishing regulatory frameworks that ensure data security, algorithmic fairness, and ethical AI use. This comprehensive approach will not only improve the deployment of AI systems but also address the underlying issues that exacerbate AMR, such as unauthorized antibiotic sales and inadequate enforcement of guidelines. …”
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Efficiently Learning an Encoder That Classifies Token Replacements and Masked Permuted Network-Based BIGRU Attention Classifier for Enhancing Sentiment Classification of Scientific... by Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Prospects of integrative and hybrid approaches to assessing undeclared work by Cymbal О. І., Ostafiichuk Ya. V.

“…The most promising approach to quantitatively assessing the scale and forms of manifestation of undeclared work, as well as identifying its leading factors, is to build an integrated system of hybrid models based on a combination of indirect and direct assessment methods with micro-simulation modeling of the processes under study. …”
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Free-form型机床的切齿优化（一）——优化模型的建立 by 张艳红, 郭九生, 王小椿

“…In this paper, Free-form style machine tool setting parameters is analyzed, and a mathematical model of optimal synthesis is established. Keeping the predetermined second-order contact parameters unchanged and optimizing third-order contact, this model can meanwhjle optimize the forth-order contact parameters, improving quality of the meshing. …”
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An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph by Jian He, Yanling Wu, Linxi Yuan, Jiangguo Qiu, Menglong Li, Xuemei Pu, Yanzhi Guo

“…Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. …”
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Integration of multi-omics profiling reveals an epigenetic-based molecular classification of lung adenocarcinoma: implications for drug sensitivity and immunotherapy response predi... by Ning Wang, Yinan Li, Yaoyao Wang, Wenting Wang

“…Using consensus clustering and random survival forest (RSF) algorithms, we established an epigenetic-based molecular classification system and constructed a prognostic model. …”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…The suggested algorithm has produced better results, which has been confirmed by statistical methods like one-way ANOVA (analysis of variance).…”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The proposed GAT model outperformed the state-of-the-art MPGCN and DNN models, achieving improvement of 86.33% and 62.71%, respectively, under 60% DG penetration condition. …”
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Prediction of outcomes following intravenous thrombolysis in patients with acute ischemic stroke using serum UCH-L1, S100β, and NSE: a multicenter prospective cohort study employin... by Ming-Ya Luo, Yang Qu, Peng Zhang, Reziya Abuduxukuer, Li-Juan Wang, Li-Chong Yang, Zhi-Guo Li, Xiao-Dong Liu, Ce Han, Dan Li, Wei-Jia Wang, Dian-Ping Lv, Ming Liu, Jian Gao, Jing Xu, Yongfei Jiang, Hai-Nan Chen, Fu-Jin Li, Li-Ming Sun, Qi-Dong Sun, Yingbin Qi, Si-Yin Sun, Yu Zhang, Zhen-Ni Guo, Yi Yang

“…Least Absolute Shrinkage and Selection Operator regression was used for feature selection, and six ML algorithms were tested. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F 1-score, calibration curve, and decision curve analysis. …”
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Named Entity Recognition in Aviation Products Domain Based on BERT by Mingye Yang, Bernadin Namoano, Maryam Farsi, John Ahmet Erkoyuncu

“…Through experiments on the constructed aviation product dataset, the model achieved a Precision value of 91.74%, a Recall value of 92.46%, and an F1 score of 92.1%, Compared with other baseline models, the F1-score is improved by 0.9% to 1.5%. …”
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Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study by Hye-Jin Kim, Heeji Choi, Hyo-Jung Ahn, Seung-Ho Shin, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae-Jun Lee

“…However, the light gradient boosting model demonstrated better performance in accuracy, recall, and F1 ConclusionsAnalyzing lifestyle behavioral factors in ASCVD risk with an ML model improves the predictive performance compared to traditional models. …”
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A novel approach for breast cancer detection using a Nesterov accelerated adam optimizer with an attention mechanism by Abeer Saber, Tamer Emara, Samar Elbedwehy, Esraa Hassan

“…The attention module improves the MobileNet-V2 model’s performance by highlighting disease-affected areas within the images. …”
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Machine Learning Detection of Melting Layers From Radar Observations by Yan Xie, Fraser King, Claire Pettersen, Mark Flanner

“…Compared to a traditional detection method, the U‐Net model increases the Probability of Detection by 57% and improves the mean Dice‐Sørensen coefficient from 0.69 to 0.91. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…Radiomics features were extracted from CT images, and 7 machine learning algorithms were used to develop 7 radiomics models, which were combined with deep learning features extracted from the ResNet50 deep learning network to form deep learning radiomics (DLR) models. …”
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Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

“…One of the most well-known nonlinear methods that is not based on the mathematical model of the wind conversion system is super-twisting control. …”
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