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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CPAP management of COVID-19 respiratory failure: a first quantitative analysis from an inpatient service evaluation by Abdul Ashish, Alison Unsworth, Jane Martindale, Kanishka Kavuri, Luigi Sedda, Martin Farrier

“…A stratified Cox proportional hazard for clustered data (via generalised estimating equations) and model selection algorithms were employed to identify the effect of CPAP on patients’ survival and the effect on gas exchange as measured by alveolar arterial (A-a) gradient and timing of CPAP treatment on CPAP patients’ survival.Results CPAP was found to be significantly (HR 0.38, 95% CI 0.36 to 0.40) associated with lower risk of death in patients with hospital stay equal to, or below 7 days. …”
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Content of Some Pro- and Anti-inflammatory Factors, Insulin Resistance Parameters in Patients with Type 2 Diabetes Mellitus and Cardiovascular Autonomic Neuropathy, Influence of Om... by Serhiyenko V., Serhiyenko О.

“…American Diabetes Association (2016) recommend the prescription of ω-3 PUFAs in algorithms of DLP treatment among patients with T2DM and cardiovascular diseases. …”
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Preoperatively-determined Red Distribution Width (RDW) predicts prolonged length of stay after single-level spinal fusion in elderly patients by Anton Früh, Dietmar Frey, Adam Hilbert, Claudius Jelgersma, Christian Uhl, Nitzan Nissimov, Peter Truckenmüller, David Wasilewski, Dimitrios Rallios, Matthias Hoppe, Simon Bayerl, Nils Hecht, Peter Vajkoczy, Lars Wessels

“…Discussion and conclusion: RDW may serve as a predictor for a pLOS in elderly. …”
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Prediction of canopy mean traits in herbaceous plants by the UAV multispectral data: The quest for a better leaf-to-canopy upscaling method by Yuanqi Shan, Yunlong Yao, Lei Wang, Zhihui Wang, Huaihu Yi, Yi Fu, Weineng Li, Xuguang Zhang, Wenji Wang, Zhongwei Jing

“…These findings contribute to advancing the prediction accuracy of plant functional traits through remote sensing techniques, while future studies may explore the integration of deep learning methods.…”
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AlphaFold-based AI docking reveals AMPK/SIRT1-TFEB pathway modulation by traditional Chinese medicine in metabolic-associated fatty liver disease by Lulu Zhang, Yi Zheng, Mingyan Shao, Aiping Chen, Meiyi Liu, Wenlong Sun, Tianxing Li, Yini Fang, Yang Dong, Shipeng Zhao, Hui Luo, Juan Feng, Qi Wang, Lingru Li, Yanfei Zheng

“…Futher analysis of their structures using AlphaFold3 algorithms, yielded high-ranking scores of 0.97 and 0.93, respectively. …”
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Associations of accelerated biological ageing with incident dementia, cognitive functions and brain structure: a prospective cohort study based on UK Biobank by Xiao Ren, Xiaowei Zheng, Yonghong Zhang, Zhengbao Zhu, Mengyao Shi, Pinni Yang, Lulu Sun, Ruirui Wang, Yiqun Li, Wenyang Han, Minglan Jiang, Yiming Jia

“…We measured biological age from clinical traits using the Klemera-Doubal method Biological Age (KDM-BA) and PhenoAge algorithms. Cox models were applied to evaluate the risk of dementia. …”
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Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approach by Elizabeth P.V. Le, Mark Y.Z. Wong, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Jonathan R. Weir-McCall, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Fulvio Zaccagna, Chris Wall, Rouchelle Sriranjan, Andrej Corovic, Yuan Huang, Elizabeth A. Warburton, Evis Sala, Michael Roberts, Carola-Bibiane Schönlieb, James H.F. Rudd

“…Though further work is required, the transition of these novel techniques into clinical practice may eventually facilitate better stroke risk stratification.…”
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Generation of field-reversed configurations via neutral beam injection by T. Roche, S. Dettrick, A. Fontanilla, S. Gupta, M. Onofri, J. A. Romero, L. C. Steinhauer, M. T. Tobin, E. M. Granstedt, L. Galeotti, S. Karbashewski, R. M. Magee, P. Yushmanov, E. Trask, H. Gota, S. Abramov, I. Allfrey, R. Andow, V. Arceo, J. Aviles, D. C. Barnes, M. Beall, N. G. Bolte, D. Bui, F. Ceccherini, R. Clary, T. DeHaas, B. Denlinger, A. Van Drie, P. Feng, D. K. Gupta, K. Hubbard, J. S. Kinley, K. Knapp, B. Koop, S. A. Korepanov, A. Korepanov, C. K. Lau, D. Lieurance, D. MacDonald, D. Madura, J. A. Margarit, J. Margo, P. Marsden Sr, T. Matsumoto, M. P. Meekins, R. Mendoza, R. Michel, H. Monkhorst, M. E. Morehouse, M. Nations, A. Necas, B. S. Nicks, R. Page, E. Parke, J. Paulson, K. Phung, T. W. Rogers, L. Schmitz, J. H. Schroeder, G. N. Settles, A. G. H. Sibley, M. Signorelli, R. J. Smith, G. L. Snitchler, V. Sokolov, Y. Song, G. Strashnoy, L. Tagney, J. B. Titus, J. Ufnal, T. Valentine, C. E. Weixel, S. Weixel, C. White, M. Wollenberg, K. Zhai, S. Ziaei, M. Tuszewski, A. Smirnov, S. Putvinski, T. Tajima, M. W. Binderbauer

“…These results establish a field-reversed configuration formation method which may offer technological and economic advantages on a path to a future fusion energy system.…”
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Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

“…Candidate biomarkers were screened using machine learning algorithms combined with 12 cytoHubba algorithms, and a diagnostic model for T2DM-related MAFLD was constructed and evaluated.The CIBERSORT method was used to investigate immune cell infiltration in MAFLD and the immunological significance of central genes. …”
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Disease progression & treatment need in sub-genotype C4 hepatitis B infection: a retrospective cohort study in the Northern Territory, Australia by Genevieve E. Martin, Kelly Hosking, Kelly Banz, Catherine Gargan, Geoff Stewart, Belinda Greenwood-Smith, Penelope Ramsay, Jaclyn Tate-Baker, Christine Connors, Paula Binks, Melita McKinnon, Prashanti Manchikanti, George Garambaka Gurruwiwi, Nicole Allard, Ashleigh Qama, Jessica Michaels, Emily Vintour-Cesar, Robert Batey, Catherine Marshall, Peter Nihill, Tammy-Allyn Fernandes, Karen Fuller, Steven Y. C. Tong, David Boettiger, Benjamin Cowie, Joshua S. Davis, Sarah Mariyalawuy Bukulatjpi, Jane Davies, on behalf of the Hep B PAST Partnership

“…Disease phase and cirrhotic status were determined algorithmically using clinical and laboratory data at two time points. …”
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Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease by Jing Xu, Hangyu Chen, Jingang Yang, Yanmin Yang, Yuan Wu, Jun Zhang, Jiansong Yuan, Tianjie Wang, Tao Tian, Jia Li, Xueyan Zhao, Xiaojin Gao, Jie Lu, Lin Li, Lei Zhang, Xuehui Li, Long Chen, Chuan He, Chaoran Dong, Jian Lin, Weixian Yang, Yuejin Yang

“…Using machine learning algorithms, we identified inflammation-related 5hmC modifications associated with disease severity and constructed a classification model based on key hydroxymethylated markers. …”
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Association between pro-inflammatory diet and fecal incontinence: a large population-based study by Haiyang Wang, Haiyang Wang, Zihan Liu, Zihan Liu, Xingfu Lu, Enyu Luan, Enyu Luan, Tingting Dong, Tingting Dong, Can Li, Can Li, Yanni Lv, Erkang Wu, Tao Shen, Tao Shen

“…Meanwhile, we identified key dietary factors for FI using multiple machine learning algorithms. Finally, we assessed the mediation role of inflammatory indicators on the association of key dietary factors with FI through mediation analysis.ResultsAfter adjustment for potential confounding variables, our results showed the highest tertile exhibited dramatically increasing prevalence of FI compared to the lower tertile (OR 1.27, 95% CI 1.06–1.53), suggesting a positive association between DII and FI. …”
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Trends, outcomes and knowledge gaps in mobile apps for reproductive endocrinology and infertility: a scoping review protocol by Alba Regina de Abreu Lima, Emerson Roberto dos Santos, Aline Russomano de Gouvêa, Natália Almeida de Arnaldo Silva Rodriguez Castro, João Daniel de Souza Menezes, Matheus Querino da Silva, Helena Landin Gonçalves Cristóvão, Cíntia Canato Martins, Jéssica Gisleine de Oliveira, Patrícia da Silva Fucuta, Alexandre Lins Werneck, Gerardo Maria de Araújo Filho, Heloisa Cristina Caldas, Vânia Maria Sabadoto Brienze, Júlio César André, Antônio Hélio Oliani

“…This scoping review distinguishes itself by systematically mapping and synthesising evidence on mobile apps specifically for reproductive endocrinology and infertility, unlike previous reviews that may not have focused exclusively on this intersection. …”
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Predicting postoperative malnutrition in patients with oral cancer: development of an XGBoost model with SHAP analysis and web-based application by Lixia Kuang, Lixia Kuang, Jingya Yu, Yunyu Zhou, Yu Zhang, Yu Zhang, Guangman Wang, Guangman Wang, Fangmin Zhang, Grace Paka Lubamba, Grace Paka Lubamba, Xiaoqin Bi, Xiaoqin Bi

“…Predictive models were developed via four supervised machine learning algorithms: logistic regression (LR), support vector machine (SVM), light gradient boosting machine (LGBM), and extreme gradient boosting (XGBoost). …”
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Optical Characterization of Coastal Waters with Atmospheric Correction Errors: Insights from SGLI and AERONET-OC by Hiroto Higa, Masataka Muto, Salem Ibrahim Salem, Hiroshi Kobayashi, Joji Ishizaka, Kazunori Ogata, Mitsuhiro Toratani, Kuniaki Takahashi, Fabrice Maupin, Stephane Victori

“…Additionally, a comparison of in situ <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><msub><mrow><mi>L</mi></mrow><mrow><mi>w</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> measurements in Tokyo Bay and the Ariake Sea with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><msub><mrow><mi>L</mi></mrow><mrow><mi>w</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> values obtained from 24 other AERONET-OC sites, as well as the inherent optical properties (IOPs) estimated through the Quasi-Analytical Algorithm version 5 (QAA_v5), identified five sites—Gulf of Riga, Long Island Sound, Lake Vanern, the Tokyo Bay, and Ariake Sea—as regions where negative <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><msub><mrow><mi>L</mi></mrow><mrow><mi>w</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> values are more likely to occur. …”
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Prospective Validation of Glial Fibrillary Acidic Protein, d‐Dimer, and Clinical Scales for Acute Large‐Vessel Occlusion Ischemic Stroke Detection by Yasir Durrani, Jakob V. E. Gerstl, Danielle Murphy, Ashley Harris, Imane Saali, Toby Gropen, Shashank Shekhar, Ari D. Kappel, Nirav J. Patel, Rose Du, Rodolfo E. Alcedo Guardia, Juan C. Vicenty‐Padilla, Adam A. Dmytriw, Vitor Mendes Pereira, Saef Izzy, Allauddin Khan, Mohammed A. Aziz‐Sultan, David S. Liebeskind, Jason M. Davies, Adnan H. Siddiqui, Edoardo Gaude, Joshua D. Bernstock

“…All ambulance‐identified stroke code activations <18 hours from symptom onset were recruited at Brandon Regional Hospital (Brandon, FL) between May 2021 and August 2022. Previously determined cutoff concentrations of plasma glial fibrillary acidic protein (213 pg/mL) and d‐dimer (600 ng/mL) were used in combination with prehospital stroke scales to detect LVO. …”
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A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults by Daisu Abe, Motoki Inaji, Takeshi Hase, Eiichi Suehiro, Naoto Shiomi, Hiroshi Yatsushige, Shin Hirota, Shu Hasegawa, Hiroshi Karibe, Akihiro Miyata, Kenya Kawakita, Kohei Haji, Hideo Aihara, Shoji Yokobori, Takeshi Maeda, Takahiro Onuki, Kotaro Oshio, Nobukazu Komoribayashi, Michiyasu Suzuki, Taketoshi Maehara

“…Among several machine learning algorithms, eXtreme Gradient Boosting (XGBoost) demonstrated the highest predictive accuracy in cross-validation, with an AUROC of 0.81 (±0.07) and an AUPRC of 0.33 (±0.08). …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…Introduction The evaluation of mineral reserves is conducted using various methods, which differ in calculation algorithms, accuracy, speed, the state of the mineral, and the characteristics of exploration activities (Madani, 1997; Ahmadi, 2010). …”
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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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