Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images by Xingzhi Sun, Guotong Xie, Kun Lv, Xiaoyue Zhang, Bin Lv, Yuan Ni, Yao Ma, Fangting Li, Kangyi Yang, Jiayin Qin, Huijuan Wu

“…Purpose To develop an artificial intelligence algorithm to automatically identify the anterior segment structures and assess multiple parameters of primary angle closure disease (PACD) in ultrasound biomicroscopy (UBM) images.Design Development and validation of an artificial intelligence algorithm for UBM images.Methods:2339 UBM images from 592 subjects were collected for algorithm development. …”
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Fatness, fitness and the aging brain: A cross sectional study of the associations between a physiological estimate of brain age and physical fitness, activity, sleep, and body comp... by David Wing, Lisa T. Eyler, Eric J. Lenze, Julie Loebach Wetherell, Jeanne F. Nichols, Romain Meeusen, Job G. Godino, Joshua S. Shimony, Abraham Z. Snyder, Tomoyuki Nishino, Ginger E. Nicol, Guy Nagels, Bart Roelands

“…Methods: Using T1 weighted MRI images, we applied a novel algorithm to determine the physiological age of the brain (brain-predicted age) and the predicted age difference between this physiologically based estimate and chronological age (BrainPAD) to 551 sedentary adults aged 65 to 84 with self-reported cognitive complaint measured at baseline as part of a larger study. …”
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Cooperative UAV Scheduling for Power Grid Deicing Using Fuzzy Learning and Evolutionary Optimization by Yu-Jun Zheng, Zhi-Yuan Zhang, Jia-Yu Yan, Wei-Guo Sheng

“…The algorithm is fully parallelizable and therefore can solve the problem very efficiently based on GPU parallel acceleration. …”
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A unique, consistent identifier for alternatively spliced transcript variants. by Alberto Riva, Graziano Pesole

“…The isoform signature uniquely identifies a transcript structure, and can therefore be used as a key in databases of alternatively spliced isoforms, or to compare alternative splicing predictions produced by different methods. In this paper we present the algorithm to generate isoform signatures, we provide some examples of its application, and we describe a web-based resource to generate isoform signatures and use them in database searches.…”
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Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…The eXtreme Gradient Boosting (XGBoost) algorithm was employed to assess the influence of key environmental features, including precipitation, temperature, PM10, potential evaporation, vegetation cover, and NDVI, on BD incidence. …”
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Two-dimensional contour decomposition: Decomposing mortality differences into initial difference and trend components by age and cause of death by Dmitri A. Jdanov, Domantas Jasilionis, Vladimir Shkolnikov

“…., causes of death or educational structure. METHODS: We use a step-wise replacement algorithm. …”
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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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An Innovative Proposal for Developing a Dynamic Urban Growth Model Through Adaptive Vector Cellular Automata by Ahmet Emir Yakup, Ismail Ercument Ayazli

“…For the simulation phase, an adaptive VCA-based urban growth model was developed to predict LULC changes through to 2040. The results demonstrate that the proposed algorithm can achieve a satisfactory level of accuracy in modeling urban growth.…”
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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 novelty of the work lies in the use of a developed genetic algorithm to select hyperparameters of a neural network that affect the quality of its work, but are not determined in the learning process. …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…The research applies the K-means algorithm for clustering, which enables the segmentation of exchanges based on their similarities. …”
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Modeling Universal Thermal Climate Index Thermal Stress in Iran’s Hot Zones Using Neural Networks and Naïve Bayes by Sajad Zare, Reza Esmaeili, Rasoul Hemmatjo

“…Conclusion: In the models for hot-dry regions, both algorithms predicted Ta and then Tmrt as the principal factors. …”
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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

“…The solution has been achieved by the application of KPENTA algorithm for the set of the flow equations which constitutes a pentadiagonal matrix. …”
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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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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

“…A convolutional recurrent neural network algorithm, integrating electrocardiographic (ECG) signals and features from ExECG reports, was developed to predict the risk of significant CAD. …”
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Formation of a heterogeneous group of UAVS with a reasonable number of false and real drones by Volodymyr Prymirenko, Andrii Demianiuk, Roman Shevtsov, Serhii Bazilo, Andrey Pilipenko, Mykola Vovchanskyi

“…The availability of the developed mathematical model, algorithm, and program code makes it possible to predict the possible results of the combat use of heterogeneous groups of UAVs based on the initial parameters and to substantiate recommendations for a possible composition of such groups.…”
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The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration by Yong Liu, Xueyan Chen, Jingwen Chen, Chao Song, Zhangchao Wei, Zongchao Liu, Fei Liu

“…Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM‐RFE algorithm to identify core MAPK‐related genes. …”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…The spectral data sets were analyzed using decision tree and support vector machine (SVM) algorithms to identify the most accurate model for distinguishing diseased and healthy plants. …”
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Making JavaScript Render Decisions to Optimize Security-Oriented Crawler Process by Onur Aktas, Ahmet Burak Can

“…This approach seeks to reduce computational requirements and quicken the security evaluation process through the use of machine learning algorithms. By utilizing a dataset containing the source code from the main pages of 17,160 websites, our experimental results demonstrate a 20% reduction in execution time compared to full JavaScript rendering, indicating an improvement in resource usage without any significant reduction in coverage. …”
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