Transcriptional fingerprinting of regulatory T cells: ensuring quality in cell therapy applications by Zhang Cheng, Li-Jie Wang, Yuchi Honaker, Steven A. Cincotta, Claire E. Page, Sydney Vollhardt, Victor Yuan, S. Alice Long, Yuanyuan Xiao, Joshua N. Beilke, Joseph R. Arron, Jeffrey A. Bluestone

“…We employed a non-parametric algorithm to score Treg manufacturing products for their cell identity and expansion fingerprints.ResultsThe identity fingerprint reflects Treg cell identity by effectively distinguishing Treg from Teff cells irrespective of their activation status, with 100% sensitivity and specificity, while the expansion fingerprint discriminates expanded versus endogenous Treg or Teff cells. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma by Yu Mori, Hainan Ren, Naoko Mori, Munenori Watanuki, Shin Hitachi, Mika Watanabe, Shunji Mugikura, Kei Takase

“…A support vector machine algorithm with 3-fold cross-validation was used to construct and validate the models. …”
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Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach. by Daniel U Campos-Delgado, Omar Gutierrez-Navarro, Ricardo Salinas-Martinez, Elvis Duran, Aldo R Mejia-Rodriguez, Miguel J Velazquez-Duran, Javier A Jo

“…A least squares formulation is considered for both BDE algorithms. To overcome the nonlinear interaction in the decision variables, an alternating least squares (ALS) methodology iteratively solves both estimation problems based on non-negative and constrained optimizations. …”
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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

“…A comprehensive benchmarking of 25 machine learning (ML) algorithms was conducted to evaluate their performance. …”
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Segmentasi Pelanggan B2B dengan Model LRFM Menggunakan Algoritma Fuzzy C-Means pada Rotte Bakery by Dea Putri Ananda, Siti Monalisa

“…The results revealed that there are five optimal clusters for agent customers with a DBI value of 0.57, while outlet customers have four clusters with a DBI value of 0.49. …”
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Stochastic <i>H</i>_∞ Filtering of the Attitude Quaternion by Daniel Choukroun, Lotan Cooper, Nadav Berman

“…Thanks to the bilinear structure of the quaternion state-space model, the algorithm parameters are independent of the state. …”
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R² = 0.855) and DM (R² = 0.857), while the performance for TA was unsatisfactory (R² = 0.681). …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…In contrast, classical machine learning techniques offer a more efficient alternative but are often overlooked due to a lack of focus on data pre-processing, which is critical for achieving optimal performance. Here we propose a classical machine learning system, built around a Random Forest classifier paired with a novel feature extraction algorithm adapted from Explainable Boosted Linear Regression (EBLR). …”
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Anorexia-cachexia syndrome in cancer patients: pathogenetic aspects and treatment options by A. V. Snegovoy, V. B. Larionova, I. V. Kononenko

“…First, it will allow optimizing monitoring of cancer patients predisposed to CACS development during anticancer treatment. …”
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The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods by Andrusyk Yevhenii V., Guryanova Lidiya S.

“…This market, on one hand, demonstrates exponential growth, while on the other, it develops in the context of significant economic and social challenges, which shapes a unique consumer behavior. …”
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Screening OSA in Chinese Smart Device Consumers: A Real-World Arrhythmia-Related Study by Chen Y, Zhang H, Li J, Xu P, Guo Y, Xie L

“…Age emerged as an independent predictor of arrhythmia risk, while hypertensive OSA patients were older, more obese, and experienced prolonged nocturnal hypoxia (Time length of SpO2< 90%, P=0.020). …”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…The terms ‘‘endourology’’, ‘‘artificial intelligence’’, ‘‘machine learning’’, and ‘‘urolithiasis'’ were used for searching eligible reports, while review articles, articles referring to automated procedures without AI application, and editorial comments were excluded from the final set of publications. …”
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Exploration of ductility for refractory high entropy alloys via interpretive machine learning by Shaolong Zheng, Lingwei Yang, Liyang Fang, Chenran Xu, Guanglong Xu, Yifang Ouyang, Xiaoma Tao

“…RHEAs with compressive ductility ≥30 % hold particular commercial value. While ductility can be engineered through alloying composition and processing condition optimization, this remains challenging due to the virtually infinite and vast unexplored compositional space. …”
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Discovery of Potent Dengue Virus NS2B-NS3 Protease Inhibitors Among Glycyrrhizic Acid Conjugates with Amino Acids and Dipeptides Esters by Yu-Feng Lin, Hsueh-Chou Lai, Chen-Sheng Lin, Ping-Yi Hung, Ju-Ying Kan, Shih-Wen Chiu, Chih-Hao Lu, Svetlana F. Petrova, Lidia Baltina, Cheng-Wen Lin

“…We utilized docking algorithms to evaluate the interactions of these GL derivatives with key residues (His51, Asp75, Ser135, and Gly153) within 10 Å of the DENV-2 NS2B-NS3 protease binding pocket (PDB ID: 2FOM). …”
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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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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“…The search focused on extracting data regarding the ML algorithms applied; disease categories studied; types of study designs (eg, clinical trials and cohort studies); and the sources of RWE, including EHRs, patient registries, and wearable devices. …”
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