Dictionary-based Block Encoding of Sparse Matrices with Low Subnormalization and Circuit Depth by Chunlin Yang, Zexian Li, Hongmei Yao, Zhaobing Fan, Guofeng Zhang, Jianshe Liu

“…Block encoding severs as an important data input model in quantum algorithms, enabling quantum computers to simulate non-unitary operators effectively. …”
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An Intelligent Diagnostic System to Analyze Early-Stage Chronic Kidney Disease for Clinical Application by N. I. Md. Ashafuddula, Bayezid Islam, Rafiqul Islam

“…This highlights its potential as a promising computer-aided diagnosis tool for doctors, enabling early interventions and improving patient outcomes.…”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…Moreover, the histopathology image-based deep learning model accurately predicted our LM-based LUSC taxonomy, significantly improving its clinical utility. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…An innovative semi‐supervised fundus image DR grading framework is proposed, employing a saliency estimation map to bolster the model's perception of fundus structures, thereby improving the differentiation between lesions and healthy regions. …”
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Fusion of Masked Autoencoder for Adaptive Augmentation Sequential Recommendation by SUN Xiujuan, SUN Fuzhen, LI Pengcheng, WANG Aofei, WANG Shaoqing

“…Experimental results on the Books, Toys, and Retailrocket datasets show that the recommendation accuracy of the proposed model is superior to the most advanced baseline algorithms in terms of hit ratio (HR) and normalized discounted cumulative gain (NDCG) metrics. …”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…The autoencoder extracts essential features from raw data using unlabeled data, improving the model’s ability to learn meaningful representations. …”
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Control System for U-Arm Robot Arm Movement with Linear Gripper Based on Inverse Kinematic Method by Aditya Putra Perdana Prasetyo, Ikang Rahmatullah, Kemahyanto Exaudi, Rendyansyah Rendyansyah

“…This error rate provides valuable insights into the performance and potential areas for improvement in the kinematic model. Additionally, this research includes the development of a program to control the servo motor speed using For and delay functions. …”
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Identifying Influential Nodes in Complex Networks via Transformer with Multi-Scale Feature Fusion by Tingshuai Jiang, Yirun Ruan, Tianyuan Yu, Liang Bai, Yifei Yuan

“…Through the transformer module, node information is effectively aggregated, thereby improving the model’s ability to recognize key nodes. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…In order to surpass these limitations, a new approach by using state-of-the-art machine learning algorithms such as Extreme Gradient Boosting (XGBoost) combined with Fuzzy Inference Systems (FIS) presents a new perspective towards improved accuracy and comprehensibility in fault detection. …”
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A review of recent artificial intelligence for traditional medicine by Chengbin Hou, Yanzhuo Gao, Xinyu Lin, Jinchao Wu, Ning Li, Hairong Lv, William Cheng-Chung Chu

“…By leveraging advanced algorithms and models, AI can improve decision-making efficiency, optimize diagnosis accuracy, enhance patient experience, and reduce costs. …”
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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…Mathematical models of Barnacle Mating Optimization (BMO) are based on observations of real-world barnacle mating behaviors such as sperm casting and self-fertilization. …”
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Key metrics for monitoring performance variability in edge computing applications by Panagiotis Giannakopoulos, Bart van Knippenberg, Kishor Chandra Joshi, Nicola Calabretta, George Exarchakos

“…Edge computing systems typically consist of heterogeneous processing and networking components, resulting in inconsistent task performance. To improve the consistency of edge computing applications, this study presents a method to identify the factors that affect variability in task execution time. …”
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Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…However, the presence of heat flows between areas with different specified parameters makes it difficult to adjust them. The work aims to improve the quality of thermal control in multiarea premises with a dynamic structure for the location of movable heaters. …”
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Natural language processing for enhanced feedback mechanisms in breast cancer care: a systematic review and comparative exploration by Faezeh Firuzpour, Hamid Reza Saeidnia

“…This study contributes to the growing body of knowledge on NLP applications in healthcare, highlighting its transformative potential to improve patient-centered care and inform clinical decision-making in breast cancer treatment.…”
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Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques by Obsa Gelchu Horsa, Kula Kekeba Tune

“…Using multinomial naïve Bayes, the accuracy generated in combination with both BoW and TF-IDF was 88%. To improve the optimal performance evaluation parameters, different hyperparameter tuning settings were applied. …”
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Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review by Guido Marchi, Mattia Mercier, Jacopo Cefalo, Carmine Salerni, Martina Ferioli, Piero Candoli, Leonardo Gori, Federico Cucchiara, Giovanni Cenerini, Giacomo Guglielmi, Michele Mondoni

“…Conclusions Advanced imaging techniques and AI applications show promise in the management and follow-up of pleural diseases, improving diagnostic accuracy and reducing the need for invasive procedures. …”
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Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning by Zhixiang Wang, Qingqing Li, Yiran Wang, Linxue Qian, Xiangdong Hu, Dong Liu

“…It can assist doctors in developing more effective treatment plans, improving patient outcomes. Future studies should expand sample sizes, include multicenter data, and explore advanced algorithms to further enhance diagnostic performance.…”
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Enhancing emergency response efficiency through advanced urban logistics: The role of driver psychophysiology and vehicle dynamics in mitigating socio-economic impacts by Yurii Davidich, Dávid Földes, Andrii Galkin

“…Utilising regression models and physiological assessments, we developed predictive models that link these factors to emergency response times. …”
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Research on the Enhancement and Development of the Resilience Assessment System for Underground Engineering Disaster Risk by Weiqiang Zheng, Zhiqiang Wang, Bo Wu, Shixiang Xu, Jiacheng Pan, Yuxuan Zhu

“…The integration of intelligent static assessment models based on artificial intelligence algorithms can effectively enhance the accuracy of resilience evaluations. …”
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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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