Machine Learning-Based Prediction of Feed Conversion Ratio: A Feasibility Study of Using Short-Term FCR Data for Long-Term Feed Conversion Ratio (FCR) Prediction by Xidi Yang, Liangyu Zhu, Wenyu Jiang, Yiting Yang, Mailin Gan, Linyuan Shen, Li Zhu

“…Feed conversion ratio (FCR) is a critical indicator of production efficiency in livestock husbandry. Improving FCR is essential for optimizing resource utilization and enhancing productivity. …”
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Experience in genetic testing of hypertrophic cardiomyopathy using nanopore DNA sequencing by R. R. Salakhov, M. V. Golubenko, E. N. Pavlukova, A. N. Kucher, N. P. Babushkina, N. R. Valiahmetov, A. V. Markov, E. O. Belyaeva, A. F. Kanev, M. S. Nazarenko

“…It appears that monomolecular sequencing technology is a feasible approach to identify mutations in patients with hypertrophic cardiomyopathy. Although improvement in accuracy of DNA sequencing, as well as optimization and simplification of bioinformatic algorithms for identification of the genetic variants are needed.…”
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An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndromeResearch in context by Peng Peng Xu, Bin Hu, Fan Zhou, Zhi Han Xu, Qian Chen, Tong Yuan Liu, Bang Jun Guo, Chang Sheng Zhou, Xin Wei Tao, Hong Yan Qiao, Jia Ni Zou, Xiang Ming Fang, Wen Cai Huang, Long Jiang Zhang

“…Additionally, the RF model showed a significant improvement in performance compared to the stenosis severity model in both Cohorts 3 and 4 (all net reclassification improvement [NRI] values > 0). …”
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Machine Learning-Driven GLCM Analysis of Structural MRI for Alzheimer’s Disease Diagnosis by Maria João Oliveira, Pedro Ribeiro, Pedro Miguel Rodrigues

“…Results: The cML algorithms achieved the following classification <i>accuracy</i>: 85.2% for <i>AD</i> vs. …”
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Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring by Alexandre Fuster-Calvo, Sarah Valentin, William C. Tamayo, Dominique Gravel

“…Our evaluative framework, based on predefined criteria, can be adopted by automated algorithms for streamlined prioritization, and we make our manually evaluated data publicly available, serving as a benchmark for improving classification techniques.…”
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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

“…These challenges become especially critical in domains such as pathology and blood sciences, where opaque AI algorithms and non-representative datasets can impact clinical outcomes. …”
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Dunes Identification Based on Attention Mechanism With Dual-Branch Codec by Zhaobin Wang, Yan Li, Yue Shi, Yaonan Zhang, Xuejun Guo

“…In the dual-branch structure, the overcomplete and incomplete networks can take into account both small and large receptive fields, improving the situation of local detail loss caused by the incomplete network in the traditional semantic segmentation structure. …”
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Dual-stream interactive mechanism with multi-modal hierarchical aggregation transformer for gait recognition by Jinghang Liu, Xiangyuan Xu, Yan Qiu, Chunzhi Wang

“…These issues prevent existing algorithms from fully leveraging the complementary advantages of multimodal data. …”
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Epidemiological and pharmacoeconomic aspects of HIV infection in military by Yu. I. Bulankov, M. A. Bulygin, A. V. Bespalov, K. V. Zhdanov, A. A. Murachev, K. S. Ivanov, Yu. I. Lyashenko

“…The results of the study demonstrate that a significant improvement of the epidemiological situation in the field of HIV infection in the Armed Forces is achievable at very low economic costs. …”
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Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients by Farnaz Khodami, Amanda S. Mahoney, James L. Coyle, Ervin Sejdic

“…By applying established algorithms to an unseen population, we demonstrated the utility of HRCA signals for swallowing assessment in individuals with NG tubes and showcased the generalizability of algorithms developed in our previous studies. …”
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Architecture-aware minimization (A2M): how to find flat minima in neural architecture search by Matteo Gambella, Fabrizio Pittorino, Manuel Roveri

“…A ^2 M consistently improves generalization over state-of-the-art DARTS-based algorithms on benchmark datasets including CIFAR-10, CIFAR-100, and ImageNet-16-120, across both NAS-Bench-201 and DARTS search spaces. …”
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Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data by Dev Dinesh, Shashi Kumar, Sameer Saran

“…Soil moisture is a critical factor that supports plant growth, improves crop yields, and reduces erosion. Therefore, obtaining accurate and timely information about soil moisture across large regions is crucial. …”
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ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI by Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu

“…Furthermore, it enables users to design and test custom algorithms through scripting, greatly improving its utility and extensibility. …”
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Effective Machine Learning Techniques for Dealing with Poor Credit Data by Dumisani Selby Nkambule, Bhekisipho Twala, Jan Harm Christiaan Pretorius

“…The differences in performance of all seven machine learning algorithms are significant at the 95% level.…”
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Review of Maglev Train Dynamics Research by WEN Yanfeng, ZHANG Weifeng, CAI Wenfeng, XU Hao

“…Active suspension control algorithms and passive suspension fitting models significantly impact dynamics simulation performance. …”
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Artificial intelligence and chordoma: A scoping review of the current landscape and future directions by Eddie Guo, Rafael D. Sanguinetti, Lyndon Boone, Jiawen Deng, Husain Shakil, Mehul Gupta

“…Discussion and conclusion: AI applications in chordoma management show potential in improving diagnostic accuracy, surgical planning, and prognostication. …”
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IFNet: An Interactive Frequency Convolutional Neural Network for Enhancing Motor Imagery Decoding From EEG by Jiaheng Wang, Lin Yao, Yueming Wang

“…Results: Compared with state-of-the-art MI decoding algorithms, IFNet achieves significantly superior classification performance on both datasets while improving the winner&#x2019;s result in BCIC-IV-2a by 11&#x0025;. …”
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POSSIBILITIES OF ARTIFICIAL INTELLIGENCE IN COMPUTER-AIDED DESIGN OF STAINED GLASS ART by Andrii Petrushevskyi, Yevhen Antonovych

“…With machine learning algorithms, artificial intelligence can generate unique and creative stained glass designs, taking into account contemporary trends and individual preferences of clients. …”
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Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning by Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele

“…<b>Conclusions:</b> This study demonstrates that integrating ensemble learning algorithms and explainable AI, while using a balanced dataset with feature selection, improves quantitative results and interpretability. …”
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Neurophysiological Approaches to Lie Detection: A Systematic Review by Bewar Neamat Taha, Muhammet Baykara, Talha Burak Alakuş

“…Among classification algorithms, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Convolutional Neural Networks (CNN) were frequently utilized. …”
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