Interrelationships Between Inflammatory Score, Delayed Cerebral Ischemia and Unfavorable Outcome in Patients with aSAH: A Four-Way Decomposition by Zhang P, Zhu H, Li X, Qian Y, Zhu Y, Zhang W, Yan Z, Ni H, Lin Z, Lin X, Li Z, Zhuge Q, Zeng B

“…We also further explore the mediation and interaction of DCI within the chain of events using the four-way effect decomposition.Methods: Machine learning algorithms are used for biomarker selection and constructed the inflammatory score. …”
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Low-cost phone-based LiDAR scanning technology provides sub-centimeter accuracy when measuring the main dimensions of motor-manual tree felling cuts by Stelian Alexandru Borz, Andrea Rosario Proto

“…Short-range LiDAR technology integrated in affordable mobile platforms has already been proved to produce reliable estimates on objects located in a limited space, and point cloud processing algorithms have been developed to compare two instances of the same object, potentially enabling the quantification of tree-level wood loss. …”
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Multimodal MRI radiomics-based stacking ensemble learning model with automatic segmentation for prognostic prediction of HIFU ablation of uterine fibroids: a multicenter study by Bing Wen, Chengwei Li, Qiuyi Cai, Dan Shen, Xinyi Bu, Fuqiang Zhou

“…The stacking ensemble learning model, which integrated these five algorithms, demonstrated a notable enhancement in performance, with an AUC of 0.897 (95% CI: 0.818–0.977) in the internal test set and 0.854 (95% CI: 0.759–0.948) in the external test set.ConclusionThe DL based automatic segmentation MRI radiomics stacking ensemble learning model demonstrated high accuracy in predicting the prognosis of HIFU ablation of uterine fibroids.…”
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Evolution, reconfiguration and low-carbon performance of green space pattern under diverse urban development scenarios: A machine learning-based simulation approach by Yujie Ren, Mengdie Zhou, Antian Zhu, Shucheng Shi, Hao Zhu, Yuzhu Chen, Shanshan Li, Tianhui Fan

“…In this study, we applied machine learning algorithms to model the non-linear relationships and threshold effects between green space evolution and carbon emissions/sequestration at different stages of ecological restoration in the Yangtze River Basin, China. …”
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Applying machine learning techniques to predict the risk of distant metastasis from gastric cancer: a real world retrospective study by Xinxin Qin, Binxu Qiu, Litao Ge, Song Wu, Yuye Ma, Wei Li

“…We applied six machine learning algorithms to construct a model that can predict distant metastasis of gastric cancer. …”
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Combating Corruption in Sport: Legal Aspect (Lucha contra la corrupción en el deporte: aspecto legal) by Tetiana Kolomoiets, Maxym Tkalych, Petro Melnyk, Bogdan Panchenko, Yuliia Tolmachevska

“…Therefore, legal science has a task to determine the legal algorithms for combating sports corruption both within the country and in the international arena. …”
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Relationship between stress hyperglycemia ratio and progression of non target coronary lesions: a retrospective cohort study by Shiqi Liu, Ziyang Wu, Gaoliang Yan, Yong Qiao, Yuhan Qin, Dong Wang, Chengchun Tang

“…Logistic regression models, restricted cubic spline analysis, and machine learning algorithms (LightGBM, decision tree, and XGBoost) were utilized to analyse the relationship of stress hyperglycemia ratio and non target lesion progression. …”
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Gut metatranscriptomics based de novo assembly reveals microbial signatures predicting immunotherapy outcomes in non-small cell lung cancer by David Dora, Peter Kiraly, Csenge Somodi, Balazs Ligeti, Edit Dulka, Gabriella Galffy, Zoltan Lohinai

“…We constructed Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) machine learning (ML) algorithms and comprehensive microbial profiles. Results We detected no significant differences concerning alpha-diversity, but we revealed a biologically relevant separation between the two patient groups in beta-diversity. …”
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Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean by Jérôme Gélinas Bélanger, Jérôme Gélinas Bélanger, Tanya Rose Copley, Valerio Hoyos-Villegas, Louise O’Donoughue

“…In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus (Glyma.04G167900/GmLHCA4a, Glyma.04G166300/GmPRR1a, and Glyma.04G159300/GmMDE04). …”
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Recent advances in anion exchange membrane technology for water electrolysis: a review of progress and challenges by Abdul Qayoom, Muhammad Shakeel Ahmad, H. Fayaz, Atika Qazi, Jeyraj Selvaraj, Rahadian Zainul, Krismadinata, Nasrudin Abd Rahim, Farruh Atamurotov, Thien Khanh Tran, Basma Souayeh, Natei Ermias Benti

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Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability by Sangwon Byun, Ah Young Kim, Min-Sup Shin, Hong Jin Jeon, Hong Jin Jeon, Chul-Hyun Cho, Chul-Hyun Cho

“…This study evaluated the feasibility of using machine-learning algorithms to detect stress automatically in MDD and PD patients, as well as healthy controls (HCs), based on HRV features.MethodsThe study included 147 participants (MDD: 41, PD: 47, HC: 59) who visited the laboratory up to five times over 12 weeks. …”
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Simulación de Plataformas Robóticas de Movimiento para Aplicaciones de Realidad Virtual Mediante Filtros Digitales by Sergio Casas, Cristina Portalés, Silvia Rueda, Marcos Fernández

“…However, the set-up of the so-called washout algorithms that control the generation of self-motion is a hard process, since a great deal of tests need to be performed before reaching a proper motion fidelity. …”
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The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China by Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Gu

“…Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. …”
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ϵ-Confidence Approximately Correct (ϵ-CoAC) Learnability and Hyperparameter Selection in Linear Regression Modeling by Soosan Beheshti, Mahdi Shamsi

“…Linear regression modeling is an important category of learning algorithms. The practical uncertainty of the label samples in the training data set has a major effect in the generalization ability of the learned model. …”
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Efficient virtual machine placement in cloud computing environment using BSO-ANN based hybrid technique by Pradeep Singh Rawat, Sachin Gaur, Varun Barthwal, Punti Gupta, Debjani Ghosh, Deepak Gupta, Joel JP C. Rodrigues

“…By integrating the human creative process with the data-driven predictive capabilities of ANN, our approach aims to overcome the limitations of traditional virtual machine placement algorithms, which often struggle to adapt to dynamic workloads and changing resource requirements. …”
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IL-6R Inhibitors and Gastrointestinal Perforations: A Pharmacovigilance Study and a Predicting Nomogram by Shupeng Zou, Mengling Ouyang, Qian Cheng, Xuan Shi, Yazheng Zhao, Minghui Sun

“…<b>Methods:</b> A disproportionate analysis was used to quantify the signals of GIPs caused by IL-6R inhibitors using two algorithms, and we assessed the risk using logistic regression analysis. …”
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Experimental study and model prediction of the influence of different factors on the mechanical properties of saline clay by Hui Cheng, Lingkai Zhang, Chong Shi, Pei Pei Fan

“…The boundary point of the 2% salt content divides the effect of salt ions from promoting free water flow to blocking seepage channels, with the proportion of micropores being the primary influencing factor. (4) Employing statistical theory and machine learning algorithms, dry density, water content, and salinity are used to predict mechanical index values. …”
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Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. Furthermore, model stacking and average ensemble learning methods were adopted to further improve the generalization performance of the model. …”
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Trends and Gaps in Digital Precision Hypertension Management: Scoping Review by Namuun Clifford, Rachel Tunis, Adetimilehin Ariyo, Haoxiang Yu, Hyekyun Rhee, Kavita Radhakrishnan

“…The most commonly used digital technologies were mobile phones (33/46, 72%), blood pressure monitors (18/46, 39%), and machine learning algorithms (11/46, 24%). In total, 45% (21/46) of the studies either did not report race or ethnicity data (14/46, 30%) or partially reported this information (7/46, 15%). …”
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Tantangan dan Strategi Pencegahan Konflik akibat Intoleransi dan Radikalisme di Era Digital untuk Mewujudkan Keamanan Nasional by Budi Setiawan, Bayu Setiawan, Eri R Hidayat, Pujo Widodo, Herlina Juni Risma Saragih, Achmed Sukendro

“…The results show that the main challenges in conflict prevention include anonymity and accessibility of technology, social media algorithms that support confirmation bias, lack of digital literacy, weak supervision and regulation, and the appeal of radical ideologies. …”
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