Digital transformation of modern corporation management tools: the current state and development paths by V. A. Laptev, S. Yu. Chucha, D. R. Feyzrakhmanova

“…The authors distinguish three types of digital corporate governance: remote management (exercised by human individuals), smart management (based on algorithms designed by human engineers), and artificial intelligence (AI) management (that does not require human involvement). …”
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Utilizing Artificial Intelligence (AI) for the optimal design of geothermal cogeneration systems in zero energy building by Ehsanolah Assareh, Mohammad Zoghi, Ali Zare, Hassan Bazazzadeh, Adnan Alboghobeysh, Saleh Mobayen, Nima Izadyar, Siamak Hoseinzadeh

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Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles by Anxun Zhang, Longjie Wang, Xiaowei Zhai, Yao Xiao, Yanchan Wu, Yongxi Zhao, Kai Liu, Ji‐Shen Zheng, Dong Chen

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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
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A Comparative Study of the Accuracy and Readability of Responses from Four Generative AI Models to COVID-19-Related Questions by Zongjing Liang, Yun Kuang, Xiaobo Liang, Gongcheng Liang, Zhijie Li

“…Then the neural network model in the intelligent algorithms is used to identify the factors that affect readability. …”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

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Genetic analysis of non-syndromic peg lateralis using whole-exome sequencing by Junglim Choi, Junglim Choi, Sungnam Kim, Hyunsoo Ahn, Donghyo Kim, Sung-Won Cho, Sanguk Kim, Sanguk Kim, Sanguk Kim, Jae Hoon Lee

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Simulating the root-to-shoot ratio of natural grassland biomass in China by the AutoGluon framework by Rui Guo, Xiaodong Huang, Yangjing Xiu, Minglu Che, Jinlong Gao, Shuai Fu, Qisheng Feng, Tiangang Liang

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Parameterised analysis of blade profiles within electric submersible pump for enhancing energy conversion efficiency by Hui Wang, Yang Yang, Qingchen Che, Jinghe Hou, Dunwei Liu, Leilei Ji, Ling Zhou, Hui Li, Zhaoming He

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Testicular appendix (hydatid of Morgagni) torsion in adult urological management: evaluation of treatment outcomes by I. S. Shormanov, D. N. Shedrov, D. Y. Garova, A. I. Ryzhkov

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Clusters of patients with chronic heart failure based on the analysis of body composition parameters and palliative status by V. I. Shevtsova, A. A. Pashkova, A. N. Shevtsov, Yu. V. Burenkov

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Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand by Chakrit Chawalit, Wuttichai Boonpook, Asamaporn Sitthi, Kritanai Torsri, Daroonwan Kamthonkiat, Yumin Tan, Apised Suwansaard, Attawut Nardkulpat

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GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science by Peder V. Nelson, Russanne Low, Holli Kohl, David Overoye, Di Yang, Xiao Huang, Sriram Chellappan, Farhat Binte Azam, Ryan M. Carney, Monika Falk, Joan Garriga, Larisa Schelkin, Rebecca Boger, Theresa Schwerin

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Development of a Japanese polygenic risk score model for amyloid-β PET imaging in Alzheimer’s disease by Misato Kaishima, Junichi Ito, Kentaro Takahashi, Kenji Tai, Junro Kuromitsu, Shogyoku Bun, Daisuke Ito

“…Abstract Background The use of polygenic risk scores (PRS) for predicting disease risk in Japanese populations, particularly for dementia and related phenotypes, remains markedly unexplored. …”
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Computed Tomography‐Based Habitat Analysis for Prognostic Stratification in Colorectal Liver Metastases by Chaoqun Zhou, Hao Xin, Lihua Qian, Yong Zhang, Jing Wang, Junpeng Luo

“…An unsupervised K‐means clustering algorithm classified the tumors into two clusters based on their habitat characteristics. …”
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Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma by Gang Wang, Jiaxing Zhang, Yirong Li, Yuyu Zhang, Weiwei Dong, Hengquan Wu, Jinglan Wang, Peiqing Liao, Ziqiang Yuan, Tao Liu, Wenting He

“…Three machine-learning algorithms were used to identify shared diagnostic genes. …”
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Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields by Gengming Zhang, Lihua Zhang, Yitao Wang, Chunyu Kang, Yinfei Zhou, Xiaodong Ma, Zeyuan Dai, Shaxige Wu

“…The result is subsequently incorporated into the sonar equation to develop a noise-considerate concealment effectiveness model, which serves as input for a noise-considerate A* path planning algorithm. Comparative analyses of path planning results demonstrate that, within the studied maritime domain, the noise-prioritized path exhibits a statistically significant reduction in the median detection range by approximately 17%, a 50% reduction in the minimum detection range, and a 20% reduction in the maximum detection range, relative to alternative paths planned with a fixed noise level assumption.…”
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OncoTrace‐TOO: Interpretable Machine Learning Framework for Cancer Tissue‐of‐Origin Identification Using Transcriptomic Signatures by Yang Hao, Haochun Huang, Daiyun Huang, Jianwen Ruan, Xin Liu, Jianquan Zhang

“…When applied to independent clinical tumor samples, the model achieved TOO prediction accuracies of 0.857, further validating its robustness. …”
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Environmental adaptations in metagenomes revealed by deep learning by Johanna C. Winder, Simon Poulton, Taoyang Wu, Thomas Mock, Cock van Oosterhout

“…To enhance biological interpretability of these predictions, we compared this model with a genetic algorithm (GA), which, although it had lower predictive ability, provided transparent classification rules and predictors. …”
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Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies by Kim Lauper, Denis Mongin, Nils Bürgisser, Samia Mehouachi, Clement P. Buclin, Delphine S. Courvoisier, Etienne Chalot

“…The framework was further validated on 600 paragraphs assessing ‘Calcium Pyrophosphate Deposition Disease (CPPD)’.Results The LLM-based algorithm outperformed the regex method, achieving a 92.7% (88.7%–95.4%) positive predictive value, a 96.6% (94.6%–97.8%) negative predictive value and an accuracy of 95.4% (93.6%–96.7%) for gout. …”
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