Defining analytical skills for human resources analytics: A call for standardization by Konrad Kulikowski

“…PURPOSE: Human resources (HR) analytics systems, powered by big data, AI algorithms, and information technology, are increasingly adopted by organizations to enhance HR’s impact on business performance. …”
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Study of the interval width of features for improving forecasting efficiency of the transport flow intensity by I. N. Pugachev, N. G. Sheshera, D. Yе. Grigorov

“…For a comprehensive characterization, additional analysis was necessary to conduct of the remaining independent features. New algorithmic structures were created using the Python programming language, in which the established feature interval ranges were sequentially compared in such a way as to process all possible combinations. …”
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Smart Safety Helmets with Integrated Vision Systems for Industrial Infrastructure Inspection: A Comprehensive Review of VSLAM-Enabled Technologies by Emmanuel A. Merchán-Cruz, Samuel Moveh, Oleksandr Pasha, Reinis Tocelovskis, Alexander Grakovski, Alexander Krainyukov, Nikita Ostrovenecs, Ivans Gercevs, Vladimirs Petrovs

“…We conclude by highlighting current research gaps, notably in standardizing systems and integrating with asset management, and provide recommendations for industry adoption and future research directions.…”
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A clinical benchmark of public self-supervised pathology foundation models by Gabriele Campanella, Shengjia Chen, Manbir Singh, Ruchika Verma, Silke Muehlstedt, Jennifer Zeng, Aryeh Stock, Matt Croken, Brandon Veremis, Abdulkadir Elmas, Ivan Shujski, Noora Neittaanmäki, Kuan-lin Huang, Ricky Kwan, Jane Houldsworth, Adam J. Schoenfeld, Chad Vanderbilt

“…With the increase in availability of public foundation models of different sizes, trained using different algorithms on different datasets, it becomes important to establish a benchmark to compare the performance of such models on a variety of clinically relevant tasks spanning multiple organs and diseases. …”
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Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients by Wenchao Zhou, Hui Li, Juan Zhang, Changsheng Liu, Dan Liu, Xupeng Chen, Jing Ouyang, Tian Zeng, Shuang Peng, Fan Ouyang, Yunzhu Long, Yukun Li

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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

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A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization by Kabiru O. Akande, Taoreed O. Owolabi, Sunday O. Olatunji, AbdulAzeez Abdulraheem

“…Hybrid computational intelligence is defined as a combination of multiple intelligent algorithms such that the resulting model has superior performance to the individual algorithms. …”
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Detection of Fake Instagram Accounts via Machine Learning Techniques by Stefanos Chelas, George Routis, Ioanna Roussaki

“…This addresses significant research challenges regarding the performance of and confidence in obtained results in this specific problem domain.…”
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The Comprehensive Effect of Depression, Anxiety, and Headache on Pain Intensity and Painkiller Use in Patients with Headache Analyzed by Unsupervised Clustering Using Machine Learn... by Jong-Ho Kim, Minha Ahn, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

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Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks by Ahmed Abd El Moaty Mohamed Gouda, Ehab K. I. Hamad, Aziza I. Hussein, M. Mourad Mabrook, A. A. Donkol

“…The proposed E-CNN model has been investigated across nine different scenarios from the DeepSense 6G dataset and compared against the conventional algorithms. For 64-beams Scenario 1, the E-CNN model showed an increase in average top-1 accuracy from 55.57% to 63.92%, and in case of 32-beams, the accuracy increased from 71.34 % to 82.06%. …”
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Enhancing drinking water safety: Real-time prediction of trihalomethanes in a water distribution system using machine learning and multisensory technology by Antonio J. Aragón-Barroso, David Ribes, Francisco Osorio

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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer by Erha Munai, Siwei Zeng, Ze Yuan, Dingyi Yang, Yong Jiang, Qiang Wang, Yongzhong Wu, Yunyun Zhang, Dan Tao

“…Four different machine learning (ML) algorithms were used to create prediction models for BMs in ES-SCLC patients. …”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…When compared with other algorithms, such as Faster RCNN, SSD, YOLOv3-tiny, and YOLOv5, the improved model strikes an optimal balance between parameter count, computational efficiency, detection speed, and accuracy, yielding superior results. …”
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Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

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Comparison between coronal FLASH and sagittal double echo steady state MRI in detecting longitudinal cartilage thickness change by fully automated segmentation – Data from the FNIH... by Felix Eckstein, Akshay S. Chaudhari, David J. Hunter, Wolfgang Wirth

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Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders by Ziqin Yang, Ziqin Yang, Nicole A. Teaney, Nicole A. Teaney, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Mustafa Sahin, Mustafa Sahin, Mustafa Sahin, Wardiya Afshar-Saber, Wardiya Afshar-Saber

“…Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. …”
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A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

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AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

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Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data by Alireza Farnoush, Zahra Sedighi-Maman, Behnam Rasoolian, Jonathan J. Heath, Banafsheh Fallah

“…Specifically, our models achieved an AUC of 0.611 and 0.674 for RF and DL algorithms, respectively. We hope our research provides researchers and clinicians with valuable insights and facilitates future research designs by identifying top ADR predictors (including demographic information) and practical parsimonious models.…”
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Comparison of different neurite density metrics with brain asymmetry evaluation by Ivan I. Maximov, Lars T. Westlye

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