Identification and validation of diagnostic biomarkers and immune cell abundance characteristics in Staphylococcus aureus bloodstream infection by integrative bioinformatics analys... by Junhong Shi, Li Shen, Yanghua Xiao, Cailing Wan, Bingjie Wang, Peiyao Zhou, Jiao Zhang, Weihua Han, Rongrong Hu, Fangyou Yu, Hongxiu Wang

“…Subsequently, the hub genes including DRAM1, PSTPIP2, and UPP1 were identified via three machine-learning algorithms: random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator. …”
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Association of reproductive characteristics with osteoporosis and FRAX scores in Chinese postmenopausal women: a QCT-based cross-sectional study by Yang You, Rongkun Chang, Wenlong Qiu, Jie Cheng, Danyu Zhao, Yinbin Wang, Ruopeng Mai, Feng Chang, Lijun Cai

“…Incorporating these reproductive variables into the FRAX algorithms may improve the accuracy of identifying high-risk individuals.…”
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ImmuProgML: machine learning-based dissection of cancer-immune dynamics during tumor progression to improve immunotherapy by Hanxiao Zhou, Lan Mei, Qianyi Lu, Yakun Zhang, Yue Sun, Caiyu Zhang, Han Jiang, Jiajun Zhou, Xia Li, Yunpeng Zhang, Shangwei Ning

“…Abstract Background Cancer progression involves distinct stages, with a critical tipping point marking the transition from early to advanced phases, driven by complex tumor-immune dynamics. While immunotherapy has significantly improved outcomes, current biomarker models lack integration of cancer-immune interactions and progression dynamics. …”
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MOIRA-UNIMORE Bearing Data Set for Independent Cart Systems by Abdul Jabbar, Marco Cocconcelli, Gianluca D’Elia, Davide Borghi, Luca Capelli, Jacopo Cavalaglio Camargo Molano, Matteo Strozzi, Riccardo Rubini

“…For single-cart experiments, 5 system variables were captured, while for three-cart experiments, 15 system variables were recorded along with nine vibration channels. …”
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Human and Machine: A View through Kant's Use of Regulative Reason by Ümit Taştan

“…Thus, we refer to the views of Henri Bergson and Nazif Muhtaroğlu to establish this connection. Bergson, while explaining the concept of motion, argues that the mind reaches such an idea of unity through an instinctive synthesis. …”
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Predictive Modelling of nephrotoxicity from vancomycin and piperacillin-tazobactam (VPT) combination and vancomycin as monotherapy: an artificial intelligence (AI) Approach by Dr Winnie Lee, Mr William J Bolton, Mr Richard C Wilson, Professor Pantelis Georgiou, Professor Alison H Holmes, Dr Nina Zhu, Dr Timothy M Rawson

“…Conclusion: Our results may provide clinicians with actionable insights into optimising empirical antimicrobial regimens while minimising nephrotoxicity risks through the use of AI, which can support better clinical decision-making.…”
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Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients by Wenyuan Dong, Hongcheng Jiang, Yu Li, Luo Lv, Yuxin Gong, Bao Li, Hongjie Wang, Hesong Zeng

“…Finally, three machine learning algorithms (RF, SVM and GLM) were used to identify significant risk factors. …”
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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…The Ca2 + value ranged between 12.83 and 25.85 mg/L, while the recorded Cl- value, fluctuate in a range of 7.3–22.12 mg/L. …”
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Machine Learning–Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study by Pinjie Huang, Jirong Yang, Dizhou Zhao, Taojia Ran, Yuheng Luo, Dong Yang, Xueqin Zheng, Shaoli Zhou, Chaojin Chen

“…ResultsThe incidence of postoperative complications in the training cohort was 47.44% (176/371), while the incidences in 4 external validation cohorts were 34% (17/50), 56.06% (37/66), 52.08% (25/48), and 48.17% (79/164), respectively. …”
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Tomografía geoeléctrica: dos ejemplos en la Sabana de Bogotá by Briceno Guarupe Luis Alberto, Sanín Camilo Ernesto

“…<p class="MsoNormal" style="margin-bottom: 0.0001pt;"><span style="font-size: 12.0pt; font-family: ";Arial";,";sans-serif";; mso-ansi-language: EN-US;" lang="EN-US">With the new technologies about math algorithms and software interpretation to solve the inverse problem, two examples of electric tomography were done in two different places and over quaternary deposits that correspond to Sabana de Bogota. …”
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Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study by Huiyu Yao, Zixin Cao, Liangfu Huang, Haojie Pan, Xiaomin Xu, Fucai Sun, Xi Ding, Wan Wu

“…Future research should focus on validating these findings in larger cohorts and exploring alternative machine-learning algorithms to improve diagnostic accuracy further.…”
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Resveratrol contributes to NK cell-mediated breast cancer cytotoxicity by upregulating ULBP2 through miR-17-5p downmodulation and activation of MINK1/JNK/c-Jun signaling by Bisha Ding, Jie Li, Jia-Lin Yan, Chun-Yan Jiang, Ling-Bo Qian, Jie Pan

“…Resveratrol (RES) is known for its multiple health benefits, while current understanding of its role in regulating cancer immunogenicity remains limited. …”
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PhA-MOE: Enhancing Hyperspectral Retrievals for Phytoplankton Absorption Using Mixture-of-Experts by Weiwei Wang, Bingqing Liu, Song Gao, Jiang Li, Yueling Zhou, Songyang Zhang, Zhi Ding

“…Traditional methods often fail under these circumstances, while improved machine-learning approaches are hindered by data scarcity, heterogeneity, and noise from data collection. …”
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In-Hospital Stroke in a Multidisciplinary Hospital by S. S. Petrikov, G. R. Ramazanov, S. B. Binnatova, M. V. Tikhomirova

“…Systemic TLT was performed in 1 patient (1%) with in-hospital stroke, while in out-of-hospital stroke, thrombolysis was performed in 36 patients (4.7%). …”
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‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion by Manash Sarma, Subarna Chatterjee

“…DL classifier is used for developing models of both categories while GB (Gradient Boost), SVM (Support Vector Machine) classifier based models are built to identify AD stages from NCBI participants. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…We also evaluated the performance of various algorithms (e.g., Random Forest (RF), Convolutional Neural Networks (CNN), Graph Neural Networks (GNN), and Multi-Layer Perceptron (MLP)) across these models. …”
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Development of machine learning predictive models and risk scoring system for survival in breast cancer patients with type II diabetes: a retrospective cohort study by Claire Chenwen Zhong, Junjie Huang, Zhaojun Li, Yu Jiang, Zehuan Yang, Ziwei Huang, Qi Dou, Yu Li, Martin C.S. Wong

“…The best-performing model identified key risk factors through SHAP (Shapley Additive Explanations) analysis, while the AutoScore-Survival package facilitated the creation of a risk score system. …”
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Comparative evaluation of machine learning models versus TIMI score in ST-segment-elevation myocardial infarction patients by Mohit D. Gupta, Dixit Goyal, Shekhar Kunal, Manu Kumar Shetty, M.P. Girish, Vishal Batra, Ankit Bansal, Prashant Mishra, Mansavi Shukla, Vanshika Kohli, Akul Chadha, Arisha Fatima, Subrat Muduli, Anubha Gupta, Jamal Yusuf

“…Results: Of the 1700 patients, 168 (9.88 %) had in-hospital mortality while 30-day mortality was reported in 210 (12.35 %) subjects. …”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…To increase productivity, precision, and reproducibility, researchers are increasingly integrating artificial intelligence (AI)-based techniques into IVOCT analysis pipelines. Machine learning algorithms, trained on labelled datasets, have demonstrated robust classification of various plaque types. …”
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Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy by Mauro Silvestrini, Simona Sacco, Massimo Caulo, Simona Marcheselli, Carmine Marini, Sergio Lucio Vinci, Angelo Galante, Marco Colasurdo, Raffaele Ornello, Matteo Foschi, Stefano Necozione, Mario Muselli, Paola Olimpia Achard, Luciano Fratocchi, Marco Cavallaro, Gabriele Polonara, Laura Straffi, Luca Sorrentino, Enrico Franconi, Marcello Alecci

“…Both units will independently adjudicate the best treatment option, while the latter will provide historical HF-MRI data to develop artificial intelligence algorithms for LF-MRI images interpretation (Free University of Bozen-Bolzano). …”
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