Construction and analysis of a prognostic risk scoring model for gastric cancer anoikis-related genes based on LASSO regression by Ai CHEN, Xiaowei CHEN, Yanan WANG, Xiaobing SHEN

“…Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. …”
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Molecular subtype of recurrent implantation failure reveals distinct endometrial etiology of female infertility by Jing Yang, Lingtao Yang, Ying Zhou, Fengyang Cao, Hongkun Fang, Huan Ma, Jun Ren, Chunyu Huang, Lianghui Diao, Qiyuan Li, Qionghua Chen

“…Abstract Background Recurrent implantation failure (RIF) remains a significant barrier in assisted reproductive technology (ART), where multiple transfers of high-quality embryos fail to achieve pregnancy. While embryo-related factors have been extensively investigated, the contribution of endometrial dysfunction to RIF remains poorly characterized. …”
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Efficiency and safety of the Russian-made KERATOLINK device used to treat patients with stage I–II keratoconus and pellucid marginal corneal degeneration by A. T. Khandzhyan, E. N. Iomdina, A. V. Ivanova, A. S. Sklyarova, N. V. Khodzhabekyan, I. V. Manukyan

“…The use of local UVCL and accelerated algorithms with a significant reduced exposure time improves the comfort and tolerability of the procedure, and also reduces the risk of complications. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…This multi-module collaborative architecture effectively processes multi-scale features of time series data while providing model interpretability. 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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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

“…These results demonstrate that the models can accurately predict solubility over a wide range of conditions while remaining computationally efficient compared to traditional models. …”
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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

“…Statistical and temporal parameters of discomposed EA signals using Wavelet Transform (WT) have been used as input of the ANN, while the outputs of model include the welding parameters: tool rotation speed and travel speed, as well as the tool profile. …”
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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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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Specifically, LightGCN achieves an accuracy of 0.9210, while DualGNN reaches 0.9285, both falling short of the proposed model’s performance. …”
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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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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. …”
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A national survey on how to improve the integration of traditional Chinese medicine and artificial intelligence: Attitudes and perceptions from medical staff by Yinger Gu, Xinyin Hu, Hye Won Lee, Zheng Yao, Tianyi Zhou, Nv Xia, Pingchun Yang, Jinglu Guo, Haifeng Huang, Lisi Wang, Wei Wang, Cheng Wang, Qiaoping Zhao, Lingling Lou, Wenjie Wu, Ke Ren, Guomei You, Longlong Fan, Jue Zhou, Fangfang Wang, Xiaoteng Chen, Fan Qu

“…Conclusion: The integration of TCM and AI has a brilliant and promising future, prioritizing diagnostic accuracy while addressing cultural/clinical adaptation challenges in key applications, such as syndrome differentiation systems.…”
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Construction of a circadian rhythm-related gene signature for predicting the prognosis and immune infiltration of breast cancer by Lin Ni, Lin Ni, He Li, Yanqi Cui, Wanqiu Xiong, Shuming Chen, Hancong Huang, Zhiwei Wang, Hu Zhao, Hu Zhao, Hu Zhao, Bing Wang, Bing Wang, Bing Wang

“…Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. …”
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Identification and quantification of transposable element transcripts using Long-Read RNA-seq in Drosophila germline tissues by Rebollo, Rita, Gerenton, Pierre, Cumunel, Eric, Mary, Arnaud, Sabot, François, Burlet, Nelly, Gillet, Benjamin, Hughes, Sandrine, S. Oliveira, Daniel, Goubert, Clément, Fablet, Marie, Vieira, Cristina, Lacroix, Vincent

“…Methods to identify and quantify TE transcription have mostly relied on short RNA-seq reads to estimate TE expression at the family level while using specific algorithms to discriminate copy-specific transcription. …”
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Management and outcome of whole-spine epidural abscesses – institutional case series and systematic review by Erik Schulz, Linda Bättig, Felix C. Stengel, Lorenzo Bertulli, Nader Hejrati, Maximilian Wegener, Carol Strahm, Benjamin Martens, Martin N. Stienen, Stefan Motov

“…Larger multicenter studies are needed to establish reliable treatment algorithms.…”
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Identification Method of Dynamic Propagation Process of Rock Fracture Based on Ground Penetrating Radar by CHEN Jun, ZHANG Bo, ZHUANG Xingyue, SONG Zhishu, ZHENG Jun

“…Future research should focus on developing advanced algorithms to suppress interference from non-uniform fillings, resolve dynamic coupling mechanisms, and improve the accuracy of vertical trajectory inversion. …”
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Machine Learning-Based Summer Crops Mapping Using Sentinel-1 and Sentinel-2 Images by Saeideh Maleki, Nicolas Baghdadi, Hassan Bazzi, Cassio Fraga Dantas, Dino Ienco, Yasser Nasrallah, Sami Najem

“…Additionally, the InceptionTime classifier, specifically designed for time series data, was tested exclusively with time series datasets to compare its performance against the three general machine learning algorithms (RF, XGBoost, and MLP). The results showed that XGBoost outperformed RF and MLP in classifying the three crops. …”
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Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution by Zehao Jin, Mario Pasquato, Benjamin L. Davis, Tristan Deleu, Yu Luo, Changhyun Cho, Pablo Lemos, Laurence Perreault-Levasseur, Yoshua Bengio, Xi Kang, Andrea Valerio Macciò, Yashar Hezaveh

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Neurofibromatosis-Noonan syndrome: a prospective monocentric study of 26 patients and literature review by Didier Bessis, Dominique Vidaud, Pierre Meyer, Laurence Pacot, de La Villeon G, Adeline Alice Bonnard, Yline Capri, Christine Coubes, Fanchon Herman, Didier Lacombe, Nicolas Molinari, Laura Poujade, Agathe Roubertie, Julien Van Gils, Alain Verloes, David Geneviève, Hélène Cavé, Marjolaine Willems

“…Inter-rater concordance was substantial (0.65 [95% CI = 0.56; 0.74]), while concordance between clinicians and F2G was almost perfect at (0.821 [CI 95% = 0.625; 1.000]). …”
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Machine learning-based prediction model for lung ischemia-reperfusion injury: insights from disulfidptosis-related genes by Yanpeng Zhang, Yanpeng Zhang, Yanpeng Zhang, Jingyang Sun, Jingyang Sun, Jingyang Sun, Yihan Lin, Yihan Lin, Yihan Lin, Rongxuan Jiang, Rongxuan Jiang, Rongxuan Jiang, Niuniu Dong, Niuniu Dong, Niuniu Dong, Huanhuan Dong, Huanhuan Dong, Huanhuan Dong, Peng Li, Peng Li, Peng Li, Jinteng Feng, Jinteng Feng, Jinteng Feng, Zijiang Zhu, Guangjian Zhang, Guangjian Zhang, Guangjian Zhang

“…Using the three machine learning algorithms for joint analysis, a predictive model composed of SLC7A11 and LRPPRC was constructed. …”
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