Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress by Jin-Biao Xie, Shi-Jie Huang, Tian-Bao Yang, Wu Wang, Bo-Yang Chen, Lianyi Guo

“…Summary Background Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies investigating the relationship between oxidative stress and prognosis of elderly patients with esophageal squamous cancer (ESCC). …”
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Price transmission and market integration analysis of black gram (urad dal) across major Indian states by Sukhvir Singh, Amit Guleria, Parvender Sheoran, Pankaj Sood, Vishal Mahajan, Dharminder Kumar, Satbir Singh, Gurdeep Singh, Rajesh K. Rana

“…Various statistical tools, including CAGR, decomposition analysis, instability analysis, seasonal indices, correlation analysis, Johansen co-integration, Granger causality, Vector Error Correction Model (VECM), impulse response function, and variance decomposition, were used for data analysis.ResultsThe findings indicate that black gram production and price dynamics are influenced by multiple factors. …”
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Dynamic Mechanical Characteristics of Impact Rock under the Combined Action of Different Constant Temperatures and Static and Dynamic Loads by Enlai Zhao, Enyuan Wang, Zesheng Zang, Xiaojun Feng, Rongxi Shen

“…The dynamic characteristics of the change law of the fine sandstone and the energy dissipation characteristics of the load process are analyzed, and the characteristic law of the fine sandstone surface response is analyzed using digital image correlation technology. …”
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Target Recognition Method Based on Graph Structure Perception of Invariant Features for SAR Images by Jingyi CAO, Yang ZHANG, Ya’nan YOU, Yamin WANG, Feng YANG, Weijia REN, Jun LIU

“…This method employs a dual-branch network to process multiview SAR images simultaneously using a rotation-learnable unit to adaptively align dual-branch features and reinforce invariant features with rotational immunity by minimizing intraclass feature differences. …”
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Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation by Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi

“…Patient’s HRV and EDA physiological signals were processed from raw data collected with the Empatica E4 wristband, and 33 features were extracted from the conditioned signals. …”
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Electrical and viscoelastic parameters of erythrocytes as predictors of exacerbation in inflammatory bowel diseases by M. V. Kruchinina, I. O. Svetlova, A. V. Azgaldyan, A. A. Gromov, V. M. Generalov, I. N. Yakovina, A. A. Shestov

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Comparative assessment of standalone and hybrid deep neural networks for modeling daily pan evaporation in a semi-arid environment by Mohammed Achite, Manish Kumar, Nehal Elshaboury, Aman Srivastava, Ahmed Elbeltagi, Ali Salem

“…Abstract Evaporation represents a fundamental hydrological cycle process that demands dependable methods to quantify its fluctuation to ascertain sustainable agriculture, irrigation systems, and overall water resource management. …”
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Cardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, E. D. Emtseva, A. A. Vishnevskiy

“…In addition, for the development of predictive models, we used multivariate LR (MLR), support vector machine (SVM) and random forest (RF). The models was assessed using 4 metrics: area under the ROC-curve (AUC), sensitivity, specificity, and accuracy.Results. …”
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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“…In questionnaire development, natural language processing using generative models such as ChatGPT was used to construct culturally competent scales. …”
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The detection of erosive changes in the joints of hands and feet in rheumatoid arthritis: a comparison of ultrasound and radiology methods by Olga G. Alekseeva, Alexander V. Smirnov, Svetlana I. Glukhova, Maria V. Severinova, Evgeny L. Nasonov, Alexander V. Volkov

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Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on R... by Ronghao Li, Shuai Mao, Congmin Zhu, Yingliang Yang, Chunting Tan, Li Li, Xiangdong Mu, Honglei Liu, Yuqing Yang

“…Simultaneously, the hybrid RAG framework combined dense and sparse vector representations to enhance LLMs’ comprehension of disease-related text. …”
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A radiomics-based interpretable machine learning model to predict the HER2 status in bladder cancer: a multicenter study by Zongjie Wei, Xuesong Bai, Yingjie Xv, Shao-Hao Chen, Siwen Yin, Yang Li, Fajin Lv, Mingzhao Xiao, Yongpeng Xie

“…Five radiomics-based ML models, namely logistic regression (LR), support vector machine (SVM), k-nearest neighbors (KNN), eXtreme Gradient Boosting (XGBoost) and random forest (RF), were developed. …”
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Applications of mutagenesis methods on affinity maturation of antibodies in vitro by LIU Yuan, LIN Manman, ZHANG Xiao, XU Chongxin, JIAO Linxia, ZHONG Jianfeng, WU Aihua, LIU Xianjin

“…However, by mutator strains, mutations are also produced in the vector part to cause deleterious effects. In site-directed mutagenesis, selected residues are targeted to be mutated. …”
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Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis by Meysam Alizamir, Mo Wang, Rana Muhammad Adnan Ikram, Sungwon Kim, Kaywan Othman Ahmed, Salim Heddam

“…In this study, the predictive accuracy of six different machine learning models, including Natural Gradient-based Boosting (NGBoost), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Support vector regression (SVR), Gaussian Process Regression (GPR), and Extremely Randomized Tree (ERT) was evaluated for modelling the parameter of permeate flow as a key element in system efficiency, energy consumption, and water quality using six various input combinations of feed water salt concentration, condenser inlet temperature, feed flow rate, and evaporator inlet temperature. …”
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Defending Data Poisoning Attack Through Watermarked Friendly Noise Luminosity Activated Dense Layered UNet for Classification of Lung Disease by M. Shyamala Devi, S. Priya

“…The image intensity ratio observed to be high with Luminous Masked Chest X-Ray Vector (LMC) image. To address the data poisoning attack towards security countermeasure, the LMC images are processed to form Watermarked Friendly Poison LMC (WFLMC) image by the proposed Watermarked Friendly Noise Luminosity Activated Dense U-Net (WFLDU-Net) model. …”
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Cellular senescence promotes macrophage-to-myofibroblast transition in chronic ischemic renal disease by Yu Zhao, Xiang-Yang Zhu, Wenqi Ma, Ying Zhang, Fei Yuan, Seo Rin Kim, Hui Tang, Kyra Jordan, Amir Lerman, Tamara Tchkonia, James L. Kirkland, Lilach O. Lerman

“…Cellular senescence was induced in human renal proximal tubular epithelial cells (HRPTEpiC) in vitro, and interferon-induced transmembrane protein-3 (IFITM3), a cellular senescence vector, was silenced (siRNA) or over-expressed (plasmid). …”
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Mosquito prevention strategies can improve indoor heat stress in hot climates: a case of traditional Kenyan homes by Haiwei Li, Haimavati Raman, Bernard Abong’o, Teresa Bange, Yongling Zhao, Carol Brayne, Ronita Bardhan

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A mobile hybrid deep learning approach for classifying 3D-like representations of Amazonian lizards by Arthur Gonsales da Silva, Arthur Gonsales da Silva, Roger Pinho de Oliveira, Caio de Oliveira Bastos, Caio de Oliveira Bastos, Elena Almeida de Carvalho, Bruno Duarte Gomes

“…This tool is aimed at processing and classifying three-dimensional samples of endemic lizard species from the Amazon rainforest. …”
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An ensemble strategy for piRNA identification through hybrid moment-based feature modeling by Mansoor Ahmed Rasheed, Tamim Alkhalifah, Fahad Alturise, Yaser Daanial Khan

“…Such accurate instrumentation of transposon-associated piRNA tags can considerably involve the study of small ncRNAs and support the understanding of the gametogenesis process. First, a number of moments were adopted for the conversion of the primary sequences into feature vectors. …”
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Application of Spectral Phototherapy in the Treatment of Patients with Ronchopathy and Obstructive Sleep Apnea Syndrome: a Prospective Study by Bair A. Zhigzhitov, Larisa A. Marchenkova, Vladimir B. Knyazkov, Daria D. Lebedeva, Lev G. Agasarov

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