Associations of lung function impairment and biological aging with mortality and cardiovascular disease incidence: findings from UK biobank participants by Jiali Chen, Cheng Wang, Pengyu Duan, Yonghong Bi, Yao Meng, Weiyu Feng, Zhehao Jin, Hangbing Li, Huihui Wang, Xiaoyan Li, Kun Zuo, Xiangcheng Zhao, Longfei Li, Yuling Xing, Lan Luo, Yang Yu, Miao Yu, Muyan Cui, Bing Zhang

“…PhenoAgeAccel was calculated using algorithms based on clinical biomarkers, and frailty was evaluated according to five established criteria. …”
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The role and prognostic value of PANoptosis-related genes in skin cutaneous melanoma by Huijing Feng, Linzi Jia, Yanan Ma, Pengmin Liu, Xiaoling Yang, Lina Hu, Kai Xu, Fan Yang, Dongfeng Zhang, Jian Li, Qi Mei, Fei Han

“…Prognostic genes for SKCM were derived using Cox analysis and machine learning algorithms, leading to the construction and validation of a prognostic model. …”
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The Clinical Significance of Abnormal Electroencephalography (EEG) Patterns in Patients with Neuropsychiatric Disorders Due to Anti-NMDA Receptor Encephalitis: A Comparative Study by Alvaro Moreno-Avellán, Arely Juarez-Jaramillo, Maria del Carmen Fernandez Gonzalez-Aragon, Gerardo Quiñones-Pesqueira, Luz Maria Pineda-Centeno, Mariana Espinola-Nadurille, Victoria Martinez-Angeles, Francisco Martinez-Carrillo, Veronica Rivas-Alonso, Daniel San-Juan, Jose Flores-Rivera, Jesus Ramirez-Bermudez

“…Electroencephalography (EEG) is a widely available tool for detecting abnormalities that may aid in early detection of cases that should undergo a thorough approach. …”
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Disease activity and treatment response in early rheumatoid arthritis: an exploratory metabolomic profiling in the NORD-STAR cohort by Tahzeeb Fatima, Yuan Zhang, Georgios K. Vasileiadis, Araz Rawshani, Ronald van Vollenhoven, Jon Lampa, Bjorn Gudbjornsson, Espen A. Haavardsholm, Dan Nordström, Gerdur Gröndal, Kim Hørslev-Petersen, Kristina Lend, Marte S. Heiberg, Merete Lund Hetland, Michael Nurmohamed, Mikkel Østergaard, Till Uhlig, Tuulikki Sokka-Isler, Anna Rudin, Cristina Maglio

“…Identification of biomarkers linked to clinical remission in RA is currently a challenge. Metabolomics may help to identify such biomarkers as it allows for a comprehensive exploration of disease-related variations that extends beyond the genome and proteome. …”
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Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

“…Among five machine learning algorithms, LDA model demonstrated the highest classification performance, with an AUC of 0.771. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…First, the number of experts familiar with advanced knowledge management models in this domain was relatively limited, which may affect the depth and accuracy of the responses provided. …”
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Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy by Yuemin Wu, Wei Zhang, Xiao Liang, Pengpeng Zhang, Mengzhe Zhang, Yuqin Jiang, Yanan Cui, Yi Chen, Wenxin Zhou, Qi Liang, Jiali Dai, Chen Zhang, Jiali Xu, Jun Li, Tongfu Yu, Zhihong Zhang, Renhua Guo

“…After applying four kinds of machine learning algorithms to select the key preoperative CT radiomic features, we used clinical, radiomics and habitat radiomic features to develop the clinical signature, radiomics signature and habitat radiomic signature for ICIs prognostics and irAEs prediction. …”
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A novel, rapid, and practical prognostic model for sepsis patients based on dysregulated immune cell lactylation by Chang Li, Mei He, PeiChi Shi, Lu Yao, XiangZhi Fang, XueFeng Li, QiLan Li, XiaoBo Yang, JiQian Xu, You Shang, You Shang

“…The proposed individualized prognostic model, based on dysregulated immune cell metabolism, accurately predicts early mortality and may inform optimized clinical management of septic patients.…”
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Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

“…While extending the duration of second stage can reduce primary cesarean delivery rates, it may increase maternal and neonatal morbidities as the duration progresses. …”
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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…This study developed a novel pixel-based grassland classification approach using three supervised machine learning (ML) algorithms, which were assessed in the province of Manitoba, Canada. …”
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Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Proton beam therapy for head and neck cancers traditionally employs a fixed relative biological effectiveness (RBE) of 1.1, which may underestimate actual biological effects in critical structures. …”
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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

“…To address this, we propose an iterative method based on intersection over union (IoU), integrating multiscale segmentation and nearest-neighbor classification algorithms. By leveraging a limited number of labeled pixels, this approach efficiently generates a extensive labeled data, enabling the rapid construction of a high-precision dataset. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. …”
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Rapid inference of antibiotic susceptibility phenotype of uropathogens using metagenomic sequencing with neighbor typing by Amanda C. Carroll, Leanne Mortimer, Hiren Ghosh, Sandra Reuter, Hajo Grundmann, Karel Brinda, William P. Hanage, Angel Li, Aimee Paterson, Andrew Purssell, Ashley Rooney, Noelle R. Yee, Bryan Coburn, Shola Able-Thomas, Martin Antonio, Allison McGeer, Derek R. MacFadden

“…Pairing metagenomic sequencing with genomic neighbor typing algorithms may support rapid clinically actionable results. …”
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Antibiogram use on dairy cattle for bovine respiratory disease: Factors associated with bacterial pathogen identification and prediction of bacterial recovery using machine learnin... by Hugo F. Monteiro, Alejandro Hoyos-Jaramillo, Adriana Garzon, Heather M. Fritz, Craig C. Miramontes, Isabelle M. Matos, Terry W. Lehenbauer, Sharif Aly, Fabio S. Lima, Richard V. Pereira

“…Differences in predictive abilities, factor importance, and the still limited number of predictors in these ML analyses further indicate a potential for building more robust future models once datasets are expanded and more robust algorithms are considered. Overall, correctly identifying factors that may be associated with the prevalence of BRD pathogens and, therefore, recovery of these pathogens is critical for the development of antibiogram programs for evaluation of the antimicrobial susceptibility of BRD pathogens.…”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…The dynamic label category system and in-memory data discovery mechanisms further improve the usability and accessibility of multi-source remote sensing sample datasets. Future work may focus on further optimizing the retrieval algorithms and expanding the range of supported data platforms to enhance the robustness and scalability of the system.…”
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Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review by Oksana V. Kryuchkova, Elena V. Schepkina, Natalia A. Rubtsova, Boris Y. Alekseev, Anton I. Kuznetsov, Svetlana V. Epifanova, Elena V. Zarya, Ali E. Talyshinskii

“…However, the clinical applicability may require more intensive expert inspection in healthcare institutions and evaluation of efficacy in prospective studies.…”
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An artificial intelligence model to predict mortality among hemodialysis patients: A retrospective validated cohort study by Zhong Peng, Shuzhu Zhong, Xinyun Li, Fengyi Yu, Zixu Tang, Chunyuan Ma, Zihao Liao, Song Zhao, Yuan Xia, Haojun Fu, Wei Long, Mingxing Lei, Zhangxiu He

“…Conversely, for those with a high probability of extended survival, kidney transplant surgery may present a favorable treatment option.…”
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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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HARMFUL CONDITIONS ON THE DENTAL STATUS OF POULTRY FARM WORKERS by T. Pupin, O. Kardashevska

“…The development of algorithms for diagnosis, prevention and treatment of dental diseases for this category of workers are considered as necessary. …”
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