Enhanced Brain Tumor Segmentation Using CBAM-Integrated Deep Learning and Area Quantification by Rafiqul Islam, Sazzad Hossain

“…The qualitative metrics typically analyze the overlap between predicted tumor masks and ground truth annotations, providing information on the segmentation algorithms’ accuracy and dependability. …”
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Latest Trend and Challenges in Machine Learning– and Deep Learning–Based Computational Techniques in Poultry Health and Disease Management: A Review by Shwetha V., Maddodi B. S., Vijaya Laxmi, Abhinav Kumar, Sakshi Shrivastava

“…The advancement of machine learning (ML)– and deep learning (DL)–based algorithms are boons for poultry health and disease management. …”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

“…Fast tuning, fast response and selective sensitivity of the developed algorithms are noted.…”
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Measuring the Dimension Accuracy of Products Created by 3D Printing Technology with the Designed Measuring System by Martin Pollák, Dominik Sabol, Karol Goryl

“…Comprehensive analysis of measurements in combination with advanced algorithms can provide more accurate dimensional characteristics and the prediction of defects. …”
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Impact of Advanced Agriculture Technologies and Energy Consumption on Crop Yields in Modern Agriculture Using Deep Learning Techniques by Khan Baz, Zhu Zhen, Hashmat Ali

“…First, advanced machine learning algorithms are employed to investigate the combined impact of the farming Product Complexity Index on agricultural yields. …”
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Integrated multiomics analysis identifies potential biomarkers and therapeutic targets for autophagy associated AKI to CKD transition by Yaojun Wang, Qiang Li

“…Single-cell analysis showed that ATP6V1C1 and COPA were specifically expressed in AKI and CKD, which may be related to renal fibrosis. In addition, drug prediction and molecular docking analysis proposed SZ(+)-(S)-202-791 and PDE4 inhibitor 16 as potential therapeutic agents. …”
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Hybrid LSTM–Attention and CNN Model for Enhanced Speech Emotion Recognition by Fazliddin Makhmudov, Alpamis Kutlimuratov, Young-Im Cho

“…Even though deep learning algorithms are actively used in this field, the study of sequence modeling that accounts for the shifts in emotions over time has not been thoroughly explored. …”
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Sentiment Analysis of User Reviews of the AdaKami Online Loan App from the App Store Using SVM and Naive Bayes by Wava Lativa Azzahra, Jamaludin Indra, Rahmat Rahmat, Sutan Faisal

“…The classification model was built using two machine learning algorithms, namely Support Vector Machine (SVM) and Naïve Bayes (NB). …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. …”
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H-DSAE: a hybrid technique to recognize heart disease by K. Uma Maheswari, A. Valarmathi

“…The next phase of the project will focus on developing more advanced classification and features algorithms. This will help improve the efficiency of the system.…”
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Generation of realistic input parameters for simulating atmospheric point-spread functions at astronomical observatories by Claire-Alice Hébert, Joshua E. Meyers, My H. Do, Patricia R. Burchat, LSST Dark Energy Science Collaboration

“…We make quantitative predictions for two-point correlation functions (2PCF) that are used in analyses of cosmic shear. …”
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Comprehensive prevention and control strategy for top coal fire based on the intelligent mine comprehensive management and control platform by Miao ZHAO

“…The existing fire perception and prevention technology and equipment are evaluated, and their problems are pointed out, such as incomplete perception coverage and immature early warning model algorithms. Based on these issues, a comprehensive fire prevention and control center is constructed, and a comprehensive prevention and control strategy is proposed, including fire prediction and early warning, coal spontaneous combustion prevention and treatment strategies, as well as associated disaster prevention and control, and emergency response and rescue strategy previews. …”
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A deep hybrid learning pipeline for accurate diagnosis of ovarian cancer based on nuclear morphology. by Duhita Sengupta, Sk Nishan Ali, Aditya Bhattacharya, Joy Mustafi, Asima Mukhopadhyay, Kaushik Sengupta

“…This novel Deep Hybrid Learning model, though derived from classical machine learning algorithms and standard CNN, showed a training and validation AUC score of 0.99 whereas the test AUC score turned out to be 1.00. …”
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Issues of diagnostics and treatment of abdominal pain at irritable bowel syndrome at outpatient stage of the healthcare by Yu. A. Kucheryavy, T. L. Lapina, M. A. Livzan, M. F. Osipenko

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Privacy-preserved data hiding using compressive sensing and fuzzy C-means clustering by Ming Li, Lanlan Wang, Haiju Fan

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Cultivation Method Analysis for Teachers’ Teaching Ability Driven by Artificial Intelligence Technology by Yanfang Chen, Shasha Xu

“…Aiming at the issues in BP network, this work constructs IPSO by improving the weight decay strategy and learning factor of PSO algorithm. Then, it uses IPSO to optimize the BP to construct IPSO-BP. …”
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Analysis and Application of Chinese Language and Literature Teaching Program Based on Computer Multimedia Technology by Zhaodi Wu

“…Many enterprises and industry organizations have entered the information age, and the field of higher education cannot lag behind because of its practical importance of training talents. …”
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The Value of MRI and Radiomics for the Diagnostic Evaluation of Thyroid-Associated Ophthalmopathy by Weiyi Zhou, Yan Song, Jufeng Shi, Tuo Li

“…The early diagnosis and prediction of these refractory and relapsed patients is essential. …”
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Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

“…Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. …”
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Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Moreover, compared with the mainstream algorithms with the same detection accuracy, this algorithm not only reduces the model size and significantly enhances detection efficiency but also satisfies the requirement of edge image processing of power inspection.…”
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