Sex hormones correlate with heart rate variability in healthy women and this correlation is conserved in women with well-controlled type 2 diabetes mellitus. by Adriana Robles-Cabrera, Claudia Lerma, Silvia Ruiz-Velasco Acosta, Iván Pérez-Díaz, Ruben Fossion

“…However, in regression models adjusted for age and glucose levels, only estradiol was found to be significant, and should be considered an important variable related to cardiovascular and autonomic balance in T2DM women and may provide crucial information to improve cardiovascular risk algorithms.…”
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Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. …”
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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

“…Finally, the role of deep-learning models in early complication detection and automated analysis of follow-up imaging studies is examined. …”
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Pose measurement method for coal mine drilling robot based on deep learning by Jiangnan LUO, Jianping LI, Hongxiang JIANG, Deyi ZHANG

“…This method consists of two parts: a segmentation model based on an improved PointNet++ and a point cloud registration process using the drill head and gripper. …”
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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“…ConclusionsThis systematic review highlights the significant potential of ML and big data analytics in health care, especially for improving disease prediction and management. However, to fully realize the benefits of these technologies, future research must focus on addressing the challenges of data quality, enhancing model transparency, and ensuring the broader applicability of ML models across diverse populations and clinical settings.…”
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A Novel Logarithmic Approach to General Relativistic Hydrodynamics in Dynamical Spacetimes by Mario Imbrogno, Rita Megale, Luca Del Zanna, Sergio Servidio

“…This method employs a “3 + 1” decomposition of spacetime, complemented by the “1 + log” slicing condition and Gamma-driver shift conditions, which have been shown to improve numerical stability in spacetime evolution. …”
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Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

“…Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. …”
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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

“…Machine learning (ML) algorithms have shown significant promise in disease diagnosis, but in healthcare, clinical data pose challenges: missing values, noisy inputs, and redundant features, affecting early-stage CKD prediction. …”
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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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Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment by Alp Gokhan Hossucu, Suat Ozdemir

“…A comprehensive multi-layered cloud simulation model that intricately considers both low-level edge/fog and cloud environment constraints is proposed. …”
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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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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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Measures of state support for increasing labor productivity: synchronization of state goals, interests and business opportunities by R. V. Plyusov, N. A. Bogdanova, O. L. Mitryakova, V. A. Umnov

“…The set of options interesting to companies often does not correspond to the «packaged» tools and algorithms, which reduces loyalty to the Labor Productivity project. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…Compared to classical machine learning models, the accuracy, sensitivity, F1 score, and specificity of the proposed hybrid QML model used with CHD are manifold higher.…”
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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

“…We deploy a set of single-particle analysis algorithms, designed for an electron microscopy use case, running on a Kubernetes cluster monitored by Prometheus. …”
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