Clinical Pathways Guided by Remotely Monitoring Cardiac Device Data: The Future of Device Heart Failure Management? by Joanne K Taylor, Fozia Zahir Ahmed

“…As standalone diagnostic tools, individual physiological metrics and algorithm-based systems have demonstrated utility in predicting future events, but the integration of remote monitoring data with existing clinical care pathways for device HF patients is not well described. …”
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Exploration for the physical origin and impact of chemical short-range order in high-entropy alloys: Machine learning-assisted study by Panhua Shi, Zhen Xie, Jiaxuan Si, Jianqiao Yu, Xiaoyong Wu, Yaojun Li, Qiu Xu, Yuexia Wang

“…In this study, we introduced a set of interpretable ML workflows and determined the best algorithm (kernel ridge regression (KRR)) for predicting the atomic stress in HEAs, which can deepen the understanding of the formation mechanism of CSRO. …”
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Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…On-site tests yielded 0.04m of average error in predicting the position of the coal rock interface. …”
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Potential Herb-Drug Interactions Among Elderly Nursing Home Residents in Romania by Hanna Sebesi, László István Bába, Melinda Kolcsár, Zsolt Gáll, Soma Dávid

“…AIM: Our study investigates the algorithm-predicted HDIs during herb-drug coadministration among elderly patients in nursing homes in a Romanian sample. …”
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Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study by Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson

“…The gradient boosting algorithm had the overall best performance, with excellent calibration of the predictions, and consistently showed higher sensitivity to detect SAE than the other methods. …”
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Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers by Ida Larsson, Felix Held, Gergana Popova, Alper Koc, Soumi Kundu, Rebecka Jörnsten, Sven Nelander

“…Here we present “single-cell regulatory-driven clustering” (scregclust), a method that reconstructs cellular regulatory programs from extensive collections of single-cell RNA sequencing (scRNA-seq) data from both tumors and developing tissues. The algorithm efficiently divides target genes into modules, predicting key transcription factors and kinases with minimal computational time. …”
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Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

“…The authors have developed the neural network models and carried out the study to find the optimal structure of a neural network, and the influence of specified neural networks hyperparameters on the error in predicting power consumption. The developed management methodology and technologies are applied in the structure of the software modeling system to manage the regional energy system of autonomous consumers. …”
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circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data by Petr Ryšavý, Alikhan Anuarbekov, Michaela Dostálová Merkerová, Jiří Kléma

“…However, validation data for RNA interactions are often sparse and predicted interactions contain many false positives. …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…Shapley Values are employed to interpret the contribution of individual variables to the model's predictions, considering all possible combinations of features. …”
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Twenty First Century’s Challenges, Changing Trends and Urdu Novel: A Critical Analysis by Mehroona Leghari

“…The trend of predicting the future is growing day by day. Now a strange situation is knocking on human beings doors. …”
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Eulerian Oil Spills Model Using Finite-Volume Method with Moving Boundary and Wet-Dry Fronts by Ehsan Sarhadi Zadeh, Kourosh Hejazi

“…For validation of oil spill model, predicted results are compared with experimental data from a physical modeling of oil spill in a laboratory wave basin under controlled conditions.…”
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Privacy-preserving location-based traffic density monitoring by Lei Wu, Xia Wei, Lingzhen Meng, Shengnan Zhao, Hao Wang

“…Traffic density monitoring is an important method to predict road traffic conditions, which can bring some convenience to people's travel in daily life. …”
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Graph attention networks based multi-agent path finding via temporal-spatial information aggregation. by Qingling Zhang, Peng Wang, Cui Ni, Xianchang Liu

“…An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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Tracking and climbing behavior recognition of heavy-duty trucks on roadways by Lei Tang, Jingchi Jia, Zongtao Duan, Jingyu Ma, Xin Wang, Weiwei Kong

“…The spatiotemporal information of trucks from trajectory tracking and motions learnt from behavior analysis can be employed to predict possible driving risks and generate safe motion to avoid roadway accidents. …”
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An indoor positioning method based on bluetooth array/PDR fusion using the SVD-EKF by Chenhui Li, Jie Zhen, Jianxin Wu

“…The dynamic test results in the room show that after SVD-EKF algorithm optimization, the positioning error is reduced by 0.05m, which is equivalent to the EKF algorithm. …”
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Model-Based Offline Reinforcement Learning for AUV Path-Following Under Unknown Ocean Currents with Limited Data by Xinmao Li, Lingbo Geng, Kaizhou Liu, Yifeng Zhao

“…To address this, we propose a conservative offline model-based Q-learning (CMQL) algorithm. This algorithm is robust to unknown disturbance and efficient in data utilization. …”
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Disulfidptosis-related classification patterns and tumor microenvironment characterization in skin cutaneous melanoma by Li Yang, Zi-jian Cao, Yuan Zhang, Jin-ke Zhou, Jun Tian

“…The consensus clustering algorithm was applied to categorize SKCM patients into different DRG subtypes. …”
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Modular Mobile Charging Facility Layout Optimization Method and Deployment Strategy by Jiajun ZHENG, Xiaoyu DUAN, Zechun HU, Xiaorui HU, Bin ZHU

“…Firstly, an electric vehicle user travel mechanism model is established to predict the spatial and temporal distribution of charging demand at the node level. …”
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Study on Vibration Characteristic of Trilobe Raceway Cylindrical Roller Bearing with Elastic Support by Sun Xue, Deng Sier, Zhang Yuanjun, Chen Guoding

“…Based on dynamics analysis of rolling bearing,the dynamics differential equations for cylindrical roller bearing with trilobe raceway and elastic support are established. By using the predict-correct integer algorithm with variable step,the dynamics equation is solved,and the influence of structural parameters of elastic support and working conditions on the vibration characteristics of the bearing is investigated. …”
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