LncRNAs regulates cell death in osteosarcoma by Ping’an Zou, Zhiwei Tao, Zhengxu Yang, Tao Xiong, Zhi Deng, Qincan Chen, Li Niu

“…The objective of the current study was to identify if a functional lncRNA-based gene signature exists that regulates non-apoptotic RCD. We systematically screened immune-related lncRNAs associated with ferroptosis, necroptosis, and pyroptosis using the Pearson correlation algorithm (|Pearson R|> 0.4, P < 0.01) on 88 osteosarcoma patients and 122 normal controls that were selected from the TARGET and GETx databases. …”
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Teknologi Irigasi Cerdas pada Sistem Irigasi Drip dengan Algoritma Ant Colony Optimization by Abdul Haris, Nabilla Anggraini, Hengki Sikumbang

“…An example of the application of technology in agriculture is the introduction of drip irrigation systems.  Many researchers have conducted studies and innovations in this matter to produce a better and more optimal irrigation, for example, by implementing a combination of Internet of Things (IoT) for the infrastructure, Fuzzy Logic and Artificial Neural Network (ANN) as algorithms to determine when the lid of the Solenoid Valve is open or closed.   …”
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CTAB modified SnO₂ PEDOT PSS heterojunction humidity sensor with enhanced sensitivity stability and machine learning evaluation by Poundoss Chellamuthu, Kirubaveni Savarimuthu, M Gulam Nabi Alsath, R. Krishnamoorthy, Yuvaraj T, Feras Alnaimat, Mohammad Shabaz

“…Furthermore, to validate real-time application feasibility, machine learning (ML) algorithms were implemented to model and predict sensor behavior. …”
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Weaning performance prediction in lactating sows using machine learning, for precision nutrition and intelligent feeding by Jiayi Su, Xiangfeng Kong, Wenliang Wang, Qian Xie, Chengming Wang, Bie Tan, Jing Wang

“…Precision feeding, supported by decision-making systems built on advanced predictive models, offers a promising solution to address these challenges. …”
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CytoBead ANA 2 assay - a novel method for the detection of antinuclear antibodies by Tulchinsky Roei, Gilburd Boris, Shovman Yehuda, Tocut Milena, Zeruya Eleanor, Binyaminov Ariel, Davidson Tima, Thomas Büttner, Abdullah Nasser, Juliane Michel, Stefan Rödiger, Peter Schierack, Amital Howard, Dirk Roggenbuck, Shoenfeld Yehuda, Shovman Ora

“…Abstract Detection of anti-nuclear autoantibodies (ANA) is based on a two-step algorithm including indirect immunofluorescence (IIF) on HEp2 cells and subsequent reflex/confirmatory testing for specific autoantibodies. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease by Ruijie Zhao, Yun Wang, Jiaru Wang, Zixing Wang, Ran Xiao, Ying Ming, Sirong Piao, Jinhua Wang, Lan Song, Yinghao Xu, Zhuangfei Ma, Peilin Fan, Xin Sui, Wei Song

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Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes by Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang

“…Mechanistic pathways governing gene-metabolite-lipid interactions were inferred via random walk with restart algorithms and validated by gene set enrichment analysis (GSEA). …”
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Evolutionary and expression analysis of sugar transporters from Tartary buckwheat revealed the potential function of FtERD23 in drought stress by Dili Lai, Md. Nurul Huda, Yawen Xiao, Tanzim Jahan, Wei Li, Yuqi He, Kaixuan Zhang, Jianping Cheng, Jingjun Ruan, Meiliang Zhou

“…Our systematic analysis provides a theoretical basis for the further functional characterization of sugar transporter genes to improve drought tolerance in Tartary buckwheat and its related species.…”
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Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey by Wei Gong, Wei Gong, Wei Gong, Xiaoxiao Hu, Huimin Cui, Huimin Cui, Yuxin Zhao, Yuxin Zhao, Hong Lin, Hong Lin, Hong Lin, Peng Sun, Peng Sun, Jianjun Yang, Jianjun Yang

“…Eight machine learning algorithms including logistic regression, decision tree, naive Bayes, neural network, support vector machine, random forest, XGBoost and Bayesian Ridge Regression were applied to build predictive models. …”
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Prevalence estimates of trafficking in persons using statistical definitions: a cross-sectional high-risk community survey in Cape Town, South Africa by Rumi Kato Price, Annah K Bender, Floriana H Milazzo, Edna G. Rich, Nicolette V. Roman, Sheldon X Zhang, Erica L Koegler

“…Secondary outcome measures included individual and summary measures from the two screeners.Results Our PRIF algorithm yielded a TIP lifetime prevalence rate of 17.0% and past 12-month rate of 2.9%. …”
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Development of a high-performing, cost-effective and inclusive Afrocentric predictive model for stroke: a meta-analysis approach  by M Nweke, P Oyirinnaya, P Nwoha, SB Mitha, N Mshunqane, N Govender, M Ukwuoma, SC Ibeneme

“…Relying solely on statistical significance to identify predictors may compromise algorithm performance. Also, some of the existing models include expensive biomarkers that are unsuitable for resource-limited settings. …”
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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…In addition, a prototype system for near–real-time monitoring was implemented and tested in a separate group of 4 participants. …”
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Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model by Bihua Yao, Xingyu Yu, Liannv Qiu, Er-min Gu, Siyu Mao, Lei Jiang, Jijun Tong, Jianguo Wu

“…It supports clinical decision-making with real-time risk assessment and promises broader applicability through future integration into clinical information systems.…”
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Método integral configurable y flexible de ensayo de materiales consumibles de soldadura por arco eléctrico. // Integral, flexible and shaped method for electric arc welding consum... by A. García Rodríguez

“…It is also possible to obtain electric<br />arc parameters data bases useful for search, development and valuation of methods and algorithms for real time monitoring of welding<br />quality during fixed technologic process of electric arc welding.…”
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Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…It was found that when using AB algorithms, greater accuracy is achieved, but the stability of the LSVM algorithm is higher. …”
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Comparative analysis of the frequency of comorbid diseases in axial psoriatic arthritis and other variants of axial spondyloarthritis. Data from a hospital cohort by A. A. Yanushonite, Yu. L. Korsakova, T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, M. M. Urumova, A. E. Dimitreva, S. I. Glukhova

“…These data should be considered in the choice of therapy and optimization of existing treatment algorithms.…”
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External reference pricing for medicines in Ukraine: latest trends by L. I. Kucherenko, I. V. Nizhenkovska, N. V. Sholoiko, L. O. Hala, N. O. Datsiuk

“…Different approaches, including different reference countries and price calculation algorithms, are applied for the price regulation of medicines in NEML and the “Affordable Medicines” program. …”
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Current and Future Trends of the Automotive Industry by Dieter Hermann Schramm

“…The technical prerequisites like sensors and actuators for these new systems are already available at least for application on motorways and rural regions, e.g. in Germany. …”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…., sparse spike-driven operations and bio-plausible learning rules) for improving energy efficiency and performance, thereby enabling efficient CL algorithms (e.g., unsupervised learning approach) executed in dynamically-changed environments with resource-constrained computing systems. …”
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