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

“…Furthermore, it establishes a foundation for integrating Bézier curve with advanced CFD-based optimisation algorithms, which could significantly enhance the effectiveness and efficiency of rotating machinery design in future research.…”
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Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau by Renzhe Wu, Guoxiang Liu, Xin Bao, Jichao Lv, Age Shama, Bo Zhang, Wenfei Mao, Jie Chen, Zhihan Yang, Rui Zhang

“…Glacial lakes (GLs), which serve as natural reservoirs, are also prospective sources of risk, and their risk levels are continuously increasing as a result of global climate warming. …”
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Developing and validating a machine learning-based model for predicting in-hospital mortality among ICU-admitted heart failure patients: A study utilizing the MIMIC-III database by De Su, Jie Zheng, Yue-kai Shao, Jun-ya Liu, Xin-xin Liu, Kun Yu, Bang-hai Feng, Hong Mei, Song Qin

“…LASSO regression was employed for feature selection, and various machine learning algorithms were utilized to train models, including logistic regression (LR), random forest (RF), and gradient boosting (GB), among others. …”
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Verifying the Effects of the Grey Level Co-Occurrence Matrix and Topographic–Hydrologic Features on Automatic Gully Extraction in Dexiang Town, Bayan County, China by Zhuo Chen, Tao Liu

“…Therefore, the GLCM tends to provide no benefit to automatic gully extraction with CNN-type algorithms, while topographic–hydrologic features, which are also original drivers of gullies, help determine the possible presence of water-origin gullies when optical bands fail to tell the difference between a gully and its confusing background.…”
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From Continent to Ocean: Investigating the Multi-Element and Precious Metal Geochemistry of the Paraná-Etendeka Large Igneous Province Using Machine Learning Tools by J. J. Lindsay, H. S. R. Hughes, C. M. Yeomans, J. C. Ø. Andersen, I. McDonald

“…Here, we use an unsupervised machine learning approach (featuring the PCA, t-SNE and k-means clustering algorithms) to investigate the geochemistry of a set of (primarily basaltic) onshore and offshore PELIP lavas. …”
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Utilising artificial intelligence in prehospital emergency care systems in low- and middle-income countries: a scoping review by Odhran Mallon, Odhran Mallon, Odhran Mallon, Freddy Lippert, Freddy Lippert, Willem Stassen, Marcus Eng Hock Ong, Caitlin Dolkart, Caitlin Dolkart, Thomas Krafft, Eva Pilot

“…Articles assessing dispatch forecasting were the most common, although artificial intelligence tools are also utilised in classification and disease prediction. …”
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Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California by Jason G. Su, Eahsan Shahriary, Emma Sage, John Jacobsen, Katherine Park, Arash Mohegh

“…These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. …”
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Surface Clay and Mineral Exploration Using Hyperspectral Imaging: Advanced Techniques for Geospatial Analysis by S. Raut, N. Andure, A. Kadam, A. Dongare, A. Fulari, G. M. Sayyad, S. B. Sayyad, S. K. Shaikh, S. Sawant

“…The study's findings not only enhance the understanding of mineral resources in the Udaipur region but also highlight the potential of HSI in climate change research. …”
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Construction of application platform for operational data of natural gas pipeline network by Hongtao DIAO, Weichao YU, Kaihong WANG, Huai SU, Yi ZHANG, Zhaoming YANG

“…Furthermore, deep learning algorithms and feature enhancement technologies were introduced to support the prediction of key gas volume parameters in the natural gas pipeline network. …”
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Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review by Rongrong Zhong, XiaoHui Wu, Jun Chen, Yiru Fang

“…Patients with BD generally exhibited lower activity levels than those with UD. They also tended to show higher activity in the morning and lower in the evening, while patients with UD showed the opposite pattern. …”
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Medical Data over Sound—CardiaWhisper Concept by Radovan Stojanović, Jovan Đurković, Mihailo Vukmirović, Blagoje Babić, Vesna Miranović, Andrej Škraba

“…Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…Meanwhile, existing automated detection algorithms often struggle with a trade-off between detection accuracy and model size. …”
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The effect of materials and methods of the sella turcica bottom plastic surgery after transsphenoidal pituitary adenoma surgery on the incidence of nasal liquorrhea by V. Yu. Cherebillo, Yu. I. Ryumina, A. V. Dubinina

“…Thus, over the past five years, we can note a significant decrease in the frequency of postoperative nasal liquorrhea after transsphenoidal surgery of pituitary adenomas, the emergence of many options and algorithms for closing the postoperative defect of the base of the skull to prevent and treat it. …”
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State preparation by shallow circuits using feed forward by Harry Buhrman, Marten Folkertsma, Bruno Loff, Niels M. P. Neumann

“…This model fits naturally between quantum algorithms in the NISQ era and full-fledged fault-tolerant quantum computation. …”
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Mechanisms of drug resistance to neoadjuvant chemotherapy in breast cancer by K. A. Aliev, E. Yu. Zyablitskaya, T. P. Makalish, L. E. Sorokina, E. R. Asanova

“…The presented results can serve as the basis for the creation of diagnostic algorithms that have predictive value regarding the effectiveness of NCT, and also to help identify new targets to justify the use of combined breast cancer treatments in the early stage.…”
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%diag_test: a generic SAS macro for evaluating diagnostic accuracy measures for multiple diagnostic tests by Jacques K. Muthusi, Peter W. Young, Frankline O. Mboya, Samuel M. Mwalili

“…This study evaluated the suitability of DBS from venous, microcapillary and direct spotting DBS, hence multiple diagnostic tests which were compared to plasma specimen. We also used the macro to reproduce results of published work on evaluating performance of multiple classification machine learning algorithms for predicting coronary artery disease. …”
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Development of an Artificial Neural Network-Based Image Retrieval System for Lung Disease Classification and Identification by Atul Pratap Singh, Ajeet Singh, Amit Kumar, Himanshu Agarwal, Sapna Yadav, Mohit Gupta

“…The system also incorporates image retrieval techniques, enabling the efficient searching and retrieval of relevant medical images from the database based on query inputs. …”
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The real-world analysis of adverse events with azacitidine: a pharmacovigilance study based on the FAERS and WHO-VigiAccess databases by Zhaorui Wang, Linlin Guo, Youfu He, Baiquan Zhang, Yang Wang, Juan Ding

“…Analysis from the WHO-VigiAccess database showed a ROR of 3.65 and a PRR of 3.30 for the SOC of infections and infestations.ConclusionThis research not only confirms the widely acknowledged AEs linked to azacitidine but also uncovers several potentially new safety concerns noted in actual clinical practice. …”
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Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

“…Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis by Lijuan Feng, Kaiyong Bai, Limeng He, Hao Wang, Wei Zhang

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”
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