A novel molecular classification system based on the molecular feature score identifies patients sensitive to immune therapy and target therapy by Yang Li, Yang Li, Yinan Ding, Yinan Ding, Jinghao Wang, Xiaoxia Wu, Xiaoxia Wu, Dinghu Zhang, Dinghu Zhang, Han Zhou, Han Zhou, Pengfei Zhang, Pengfei Zhang, Guoliang Shao, Guoliang Shao

“…Subsequently, machine learning algorithms were used to predict the classifications and prognoses. …”
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Long-term prognosis of 47 pediatric patients with Blau syndrome in China by Xinwei Shi, Jianghong Deng, Junmei Zhang, Xiaozhen Zhao, Yinan Zhao, Li Li, Fengqiao Gao, Weiying Kuang, Jiang Wang, Xiaohua Tan, Chao Li, Shipeng Li, Caifeng Li

“…A Bayesian network was constructed to integrate prediction algorithms of genetic mutations and clinical manifestations, exploring the complex relationship between genotype and phenotype through R (Version 4.4.1, R Core Development Team). …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

“…A novel framework named Spatio-Temporal Cluster-Optimized Feature Selection (STCO-FS) is proposed to identify key immediate (short-term) HW drivers by combining clustering algorithms with an ensemble evolutionary algorithm. …”
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Mechanisms for Secure Access to Data of Scientometric Systems Using Virtual DBMS by Alexander Kozitsin, Maxim Zanchurin

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Elevation of transaminases. What if not the liver? by I. V. Sharkova

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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

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Application of Serial Crystallography for Merging Incomplete Macromolecular Crystallography Datasets by Ki Hyun Nam

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Analyse des discours à l’aide des techniques d’apprentissage automatique by لمياء خي

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Diagnostics-linked Antimicrobial Surveillance: A Route to Patient-Centred Microbiology Diagnostics? by Dr Alex Howard, Dr Charlotte Brookfield, Dr Conor Rosato, Dr Anoop Velluva, Dr Alessandro Gerada, Professor William Hope

“…In this study we trialled a microbiology diagnostics-linked antimicrobial surveillance (DLAS) algorithmic approach on real-world urine antimicrobial susceptibility testing and antimicrobial prescribing data. …”
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AI illuminates paths in oral cancer by Devesh U. Kapoor, Pushpendra Kumar Saini, Narendra Sharma, Ankul Singh, Bhupendra G. Prajapati, Gehan M. Elossaily, Summya Rashid

“…The review also encompasses the utilization of artificial intelligence such as automated image analysis, computer-aided detection and diagnosis integration of machine learning algorithms for oral cancer diagnosis and treatment. …”
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NETosis-based prognostic model reveals immune modulation in clear cell renal cell carcinoma using single-cell and bulk RNA sequencing by Zijie Yu, Zihao Xu, Xi Zhang, Wenchuan Shao, Da Zhong, Xinghan Yan, Tingfei Jiang, Yichun Wang, Ninghong Song

“…We developed a prognostic framework for netosis using univariate, Lasso, and multivariate Cox regression analyses. The CIBERSORT algorithm was employed to compute immune infiltration metrics for The Cancer Genome Atlas (TCGA) dataset. …”
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Differences in Characteristics of Peripartum Patients Who Did and Did Not Require an Upgrade to the Intensive Care Unit: A Propensity Score Matching Study by Jennifer A. Walker, Jerry M. Yang, Saad Pirzada, Manahel Zahid, Samantha Asuncion, Amanda Tuchler, Gillian Cooper, Allison Lankford, Emad Elsamadicy, Quincy K. Tran

“…The Classification And Regression Tree, a machine learning algorithm, was used to identify significant predictors of ICU upgrade. …”
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Improved leaf area index reconstruction in heavily cloudy areas: A novel deep learning approach for SAR-Optical fusion integrating spatiotemporal features by Mingqi Li, Pengxin Wang, Kevin Tansey, Fengwei Guo, Ji Zhou

“…Secondly, the 2D CNN-Transformer predicted LAI and the Sentinel-2 LAI are input into the Enhanced Deep Convolutional Model for Spatiotemporal Image Fusion (EDCSTFN) model to further improve the accuracy. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We concluded that the nonlinear Gaussian process regression model with the VIs and TFs-PC1 combination selected by maximal information coefficient as input achieved the highest accuracy in LCC prediction for banana, with the highest R2 of 0.776 and lowest RMSE of 2.04. …”
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A comprehensive investigation of the relationship between dietary fatty acid intake and preserved ratio impaired spirometry: multimethodology based on NHANES by Chenyuan Deng, Yu Jiang, Yuechun Lin, Hengrui Liang, Wei Wang, Jianxing He, Ying Huang

“…Subsequently, innovative implementation of the principal component analysis (PCA), Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR) approaches were employed to assess the joint impact of the various intake of FAs, as well as total saturated, monounsaturated, and polyunsaturated FAs on PRISm. To facilitate the prediction of PRISm, six distinct machine learning algorithms were constructed, followed by the application of SHAP analysis to elucidate the contribution of individual predictors. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

“…Despite significant progress in the models’ technical implementation and predictive accuracy, in many cases, mechanisms for equity, transparency, and citizen participation have been poorly implemented. …”
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Radiomics-based differentiation of upper urinary tract urothelial and renal cell carcinoma in preoperative computed tomography datasets by Julian Marcon, Philipp Weinhold, Mona Rzany, Matthias P. Fabritius, Michael Winkelmann, Alexander Buchner, Lennert Eismann, Jan-Friedrich Jokisch, Jozefina Casuscelli, Gerald B. Schulz, Thomas Knösel, Michael Ingrisch, Jens Ricke, Christian G. Stief, Severin Rodler, Philipp M. Kazmierczak

“…Abstract Background To investigate a non-invasive radiomics-based machine learning algorithm to differentiate upper urinary tract urothelial carcinoma (UTUC) from renal cell carcinoma (RCC) prior to surgical intervention. …”
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Integrated System of Microalgae Photobioreactor and Wine Fermenter: Growth Kinetics for Sustainable CO₂ Biocapture by María Carla Groff, Cecilia Fernández Puchol, Rocío Gil, Lina Paula Pedrozo, Santiago Albareti, Ana Belén Manzanares, Emilia Sánchez, Gustavo Scaglia

“…Mathematical models are crucial for predicting microalgal growth kinetics and thus assessing their potential as industrial CO₂ sequestration agents under controlled conditions. …”
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Exploring the Shared Genetic Characteristics of Peri-Implantitis and Osteoporosis: A Transcriptomic Analysis Perspective by Churen Zhang, Feixiang Wang, Jianguo Ke, Cuihong Lin, Xiaohua Zeng, Qiuyan Yang, Qiaoling Cai

“…Potential drugs related to the hub genes were predicted using the Genecards database. Finally, the CIBERSORT core algorithm was used to calculate immune cell infiltration levels. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). …”
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