Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma by Jiani Wang, Xiaopeng Chen, Donghao Wu, Changchang Jia, Qinghai Lian, Yuhang Pan, Jiumei Yang

“…In addition, the abundance of infiltrating cells in the tumor microenvironment was investigated using single-sample gene set enrichment analysis, CIBERSORT, xCELL, and tumor immunophenotype algorithms. The expression of glycosylphosphatidylinositol anchor attachment 1 (GPAA1) was examined in the clinical sample of HCC by quantitative real-time polymerase chain reaction, Western blotting, and immunohistochemical staining. …”
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PLANNING IN ARTIFICIAL INTELLIGENCE AND ROBOTICS (PAIR) by Editorial, Foreword

“…The topics of the student presentations range from fundamental problems of mobile robotics such simultaneous localization and mapping, planning algorithms, decentralized exploration but also address high-level data managing for guiding humans or autonomous vehicles. …”
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Antarctic Ice Sheet grounding line discharge from 1996–2024 by B. J. Davison, A. E. Hogg, T. Slater, R. Rigby, N. Hansen

“…We calculate ice flux through 16 algorithmically generated flux gates across 998 ice sheet, glacier, ice stream and ice shelf drainage basins. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…Through comparative analysis of various optimization algorithms’ convergence performance and prediction accuracy, this study found that the AdamW optimizer, with its effective weight decay mechanism and adaptive learning rate, demonstrated superior performance in training stability and generalization capability, with MSE and R2 metrics outperforming traditional optimizers. …”
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An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto, Geraldo Pereira Rocha Filho

“…The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. …”
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Predicting CO₂ and H₂ Solubility in Pure Water and Various Aqueous Systems: Implication for CO₂–EOR, Carbon Capture and Sequestration, Natural Hydr... by Promise O. Longe, David Kwaku Danso, Gideon Gyamfi, Jyun Syung Tsau, Mubarak M. Alhajeri, Mojdeh Rasoulzadeh, Xiaoli Li, Reza Ghahfarokhi Barati

“…The explicit, derivative–continuous nature of these models eliminates the need for iterative algorithms, making them suitable for integration into large–scale multiphase flow simulations. …”
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Multi-omic signatures of host response associated with presence, type, and outcome of enterococcal bacteremia by Charlie Bayne, Dominic McGrosso, Concepcion Sanchez, Leigh-Ana Rossitto, Maxwell Patterson, Carlos Gonzalez, Courtney Baus, Cecilia Volk, Haoqi Nina Zhao, Pieter Dorrestein, Victor Nizet, George Sakoulas, David J. Gonzalez, Warren Rose

“…Altogether, this study aims to culminate in the creation of objective risk stratification algorithms—a pivotal step toward enhancing patient management and care. …”
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Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma by Qiang Liu, Huiguo Chen, Dongfang Tang, Huibiao Zhang, Shaogeng Chen, Yiran Meng, Boying Zheng, Fei Liu, Jing Zhou, Wen Zhang

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”
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Emisión Acústica y Redes Neuronales para Modelado y Caracterización del Proceso de Soldadura por Fricción Agitación by Emilio Jiménez Macías, Angel Sánchez Roca, Hipólito Carvajal Fals, Julio Blanco Fernández, Juan C. Sáenz-Diez Muro

“…A multilayer feed-forward ANN has been selected and trained, using different algorithms and network architectures. The parameters provided by the ANN constitute the model and the characterization of the FSW process; finally an analysis of the comparison between the measured and the calculated data is presented, validating the results. …”
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Contrast-enhanced ultrasound radiomics model for predicting axillary lymph node metastasis and prognosis in breast cancer: a multicenter study by Shi Yu Li, Yue Ming Li, Yong Qi Fang, Zhi Ying Jin, Jun Kang Li, Xiao Meng Zou, Si Si Huang, Rui Lan Niu, Nai Qing Fu, Yu Hong Shao, Xuan Tong Gong, Mao Ran Li, Wei Wang, Zhi Li Wang

“…LASSO regression was employed to select radiomic features (RFs), while eight machine learning algorithms were utilized to construct radiomic models based on US, CDFI, and CEUS. …”
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Utilizing bioinformatics to identify biomarkers and analyze their expression in relation to immune cell ratios in femoral head necrosis by Dongchen Li, Dongchen Li, Zhilong Huang, Teng Ma, Yu Su, Yu Su, Zhao Li, Zhao Li, Liang Sun, Ming Li, Zhong Li, Yao Li, Qian Wang, Yao Lu

“…Subsequently, CIBERSORT was utilized to assess the proportion and distribution of immune cell types, followed by the identification of critical Hub immune cells using LASSO and RFE algorithms. The dataset GSE123568 was then explored to identify significantly differentially expressed genes (DEGs). …”
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Machine learning applications in forecasting patient satisfaction and clinical outcomes after carpal tunnel release: a retrospective study by Zohreh Manoochehri, Sara Manoochehri, Seyed Reza Bagheri, Alireza Abdi, Ehsan Alimohammadi

“…Four machine learning algorithms—random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), and k-nearest neighbors (k-NN)—were used to predict these outcomes. …”
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Human responses to the DNA prime/chimpanzee adenovirus (ChAd63) boost vaccine identify CSP, AMA1 and TRAP MHC Class I-restricted epitopes. by Harini Ganeshan, Jun Huang, Maria Belmonte, Arnel Belmonte, Sandra Inoue, Rachel Velasco, Santina Maiolatesi, Keith Limbach, Noelle Patterson, Marvin J Sklar, Lorraine Soisson, Judith E Epstein, Kimberly A Edgel, Bjoern Peters, Michael R Hollingdale, Eileen Villasante, Christopher A Duplessis, Martha Sedegah

“…Individual antigen-specific 15mers in the subpools with strong responses were then deconvoluted, evaluated for activities, and MHC Class I-restricted epitopes within the active 15mers were predicted using NetMHCpan algorithms. The predicted epitopes were synthesized and evaluated in the FluoroSpot IFN-γ and GzB assays.…”
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Chemoreactome screening of aquacobalamin and heptamethyl ester of cyanoaquacobyrinic acid cytotoxic effects on tumor cells with experimental confirmation on BT-474 and A549 cell by I. Yu. Torshin, M. V. Filimonova, O. A. Gromova, L. A. Maiorova, M. A. Sorokina, D. E. Frolova, A. N. Gromov, I. A. Reyer

“…Chemoreactome screening was carried out on the basis of a problem-oriented theory of chemograph isomorphism analysis, which is an extension of the algebraic approach to machine learning and recognition problems. Trainable algorithms for calculating chemical distances between molecules were used, on the basis of which the values of half-maximal inhibitory concentration (IC50) were calculated. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Through experimentation, our multimodal system has made significant strides in understanding user intent based on input keywords, demonstrating superiority over classic multimodal recommendation algorithms such as Blip2, clip. This indicates that our system can intelligently generate suggestions, meeting user requirements and enhancing user experience. …”
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MicroRNA-125a-5p plays a role as a tumor suppressor in lung carcinoma cells by directly targeting STAT3 by Lou Zhong, Siyuan Sun, Jiahai Shi, Fei Cao, Xiao Han, Zhong Chen

“…The downregulation of miR-125a-5p provided very contrasting results. Computational algorithms predicted that the STAT3 is a target of miR-125a-5p. …”
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The association between metabolomic profiles of lifestyle and the latent phase of incident chronic kidney disease in the UK Population by Tingting Jin, Yunqi Wu, Siyi Zhang, Ya Peng, Yao Lin, Saijun Zhou, Hongyan Liu, Pei Yu

“…A total of 249 biological metabolites covering multiple categories were determined by the NMR Metabolomics Platform. Random forest algorithms and LASSO regression were employed to identify lifestyle-related metabolites. …”
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Penerapan Decision Tree dan Random Forest dalam Deteksi Tingkat Stres Manusia Berdasarkan Kondisi Tidur by Sza Sza Amulya Larasati, Elok Nuraida Kusuma Dewi, Brahma Hanif Farhansyah, Fitra Abdurrachman Bachtiar, Fajar Pradana

“…Hyperparameter tuning is done using k-fold cross-validation, and the model is designed using the Decision Tree and Random Forest classification algorithms. The results show that five features: snoring rate, respiration rate, limb movement including eye movement, and heart rate during sleep are directly proportional to the level of stress. …”
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Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis by Yingquan Ye, Yingquan Ye, Haili Jiang, Haili Jiang, Yue Wu, Yue Wu, Gaoxiang Wang, Gaoxiang Wang, Yi Huang, Yi Huang, Weijie Sun, Mei Zhang, Mei Zhang

“…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”
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Root-Zone Salinity in Irrigated Arid Farmland: Revealing Driving Mechanisms of Dynamic Changes in China’s Manas River Basin over 20 Years by Guang Yang, Xuejin Qiao, Qiang Zuo, Jianchu Shi, Xun Wu, Alon Ben-Gal

“…The driving mechanisms behind root-zone <i>SSC</i> distributions were analyzed using an approach combined with two machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP), to identify influential factors and quantify their impacts. …”
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