The systemic oxidative stress index predicts clinical outcomes of esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy by Jifeng Feng, Jifeng Feng, Liang Wang, Xun Yang, Qixun Chen, Qixun Chen

“…Then, a new staging that included TNM and SOSI based on RPA algorithms was produced. In terms of prognostication, the RPA model performed significantly better than TNM classification.ConclusionSOSI is a simple and useful score based on available SOS-related indices. …”
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Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

“…Two machine learning algorithms, Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine Recursive Feature Elimination (SVM-RFE), were used to screen for overlapping FRDEGs in CS and AS. …”
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Elucidating the dynamic tumor microenvironment through deep transcriptomic analysis and therapeutic implication of MRE11 expression patterns in hepatocellular carcinoma by Ruiqiu Chen, Chaohui Xiao, Zizheng Wang, Guineng Zeng, Shaoming Song, Gong Zhang, Lin Zhu, Penghui Yang, Rong Liu

“…Publicly available single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics were utilized to explore MRE11’s dynamic mechanisms in the tumor microenvironment (TME) of both primary and post-immunotherapy cases. We also screened for differentially expressed genes and constructed a robust HCC prognosis model using 101 machine-learning algorithms. …”
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Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis by Dongxu Qin, Yongquan Zheng, Libo Wang, Zhenyi Lin, Yao Yao, Weidong Fei, Caihong Zheng

“…Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify key genes. Machine learning algorithms, including Random Forest (RF) and XGBoost, were utilized to screen for shared diagnostic genes, which were subsequently validated through receiver operating characteristic (ROC) analysis and clinical prediction models. …”
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Bioinformatic analysis, clinical implications and experimental validation of ferroptosis-related feature gene in IgA nephropathy: focus on DUSP1 by Tingting Liu, Tingting Pan, Mingxin Chang, Shaojie Fu, Hongzhao Xu, Hao Wu, Zhonggao Xu, Yanli Cheng

“…Among them, dual specificity phosphatase 1 (DUSP1) was screened as FFG by three machine learning algorithms. …”
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Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila. by Jean-Baptiste Masson, François Laurent, Albert Cardona, Chloé Barré, Nicolas Skatchkovsky, Marta Zlatic, Tihana Jovanic

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Biochemical disturbances in schizophrenia — a «window of opportunity» by T. V. Zhilyaeva, A. S. Piatoikina, E. D. Kasyanov, G. V. Rukavishnikov, I. V. Semennov, O. V. Kostina, A. S. Blagonravova, G. E. Mazo

“…At the same time, there are no studies with an assessment of a wide range of correctable biochemical abnormalities in one sample of patients. Moreover, screening algorithms for the detection and personalized correction of controlled biomarkers have not been introduced into clinical practice yet.   …”
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Single-cell profiling of SLC family transporters: uncovering the role of SLC7A1 in osteosarcoma by Yan Liao, Junkai Chen, Hao Yao, Ting Zheng, Jian Tu, Weidong Chen, ZeHao Guo, Yutong Zou, Lili Wen, Xianbiao Xie

“…Multiple analytical algorithms indicated that SLCs were associated with immune cell infiltration and immune checkpoint gene expression. …”
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Combined Analysis of Transcriptome and Mendelian Randomization Reveals AKT1 and PPARG as Biomarkers Related to Glucose Metabolism in Sepsis by Ma J, Li W, Ma Q, Ding L, Wang Z, Wang R, Huang Y, Ma G, Gao J

“…Jie Ma,1,2,* Wendi Li,3 Qianqian Ma,1 Liying Ding,4 Zhaoyun Wang,1 Rong Wang,1 Yanan Huang,1 Gang Ma,2,* Jun Gao1,* 1Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China; 2Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China; 3Department of Child Rehabilitation Education, Ningxia Rehabilitation Center for the Disabled, Yinchuan, Ningxia, 750002, People’s Republic of China; 4Department of Gynecology, Gynecology Clinic of Li Ying, Wuzhong, Ningxia, 751100, People’s Republic of China*These authors contributed equally to this workCorrespondence: Gang Ma, Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China, Email magang2671@163.com Jun Gao, Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China, Email gaojun1605@sina.comIntroduction: This study aimed to identify diagnostic and therapeutic biomarkers related to glucose metabolism in sepsis, as hyperglycemia and blood glucose fluctuations influence sepsis progression.Methods: Datasets from public databases were analyzed using various methods, including differential expression analysis, PPI network screening, machine learning algorithms and Mendelian randomization. …”
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Long-term risk of de novo malignancy with tumor necrosis factor alpha (TNF) inhibitor immunosuppression: a multicenter, retrospective cohort study by Conor B. Driscoll, Jordan M. Rich, Christopher Yang, Joseph Nicolas, Dylan Isaacson, Philip Silberman, Xinlei Mi, Sai Kaushik Shakar Ramesh Kumar, Hui Zhang, Steven Belknap, William H. Temps, Edward M. Schaeffer, Shilajit D. Kundu

“…There may need to be differential cancer screening algorithms for patients with different inflammatory conditions and TNF-I exposure.…”
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Different strokes: differences in the characteristics and outcomes of BCVI and non-BCVI strokes in trauma patients by Lillian S Kao, Charles E Wade, Xu Zhang, Bryan A Cotton, Sean I Savitz, Michelle K McNutt, Cedar Slovacek, David Rosenbaum, Hari Kishan Reddy Indupuru, John Harvin

“…Blunt cerebrovascular injury (BCVI)–related strokes and mortality have decreased, likely due to refined screening and treatment algorithms in trauma literature; however, there is a paucity of research addressing non-BCVI strokes in trauma. …”
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Polygraph and audio synchronization applied to apnea event analysis based on non-negative matrix factorization by Francisco David Gonzalez-Martinez, Juan De La Torre-Cruz, Julio Jose Carabias-Orti, Francisco Jesus Canadas-Quesada, Alejandro Antonio Salvador-Navarro, Jose Ranilla, Lyam Lamrini-H. Laarbi

“…The proposed method introduces an iterative time-alignment algorithm based on the cross-correlation between an estimated respiratory sound signal and the nasal flow signal from PG. …”
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New insights into biomarkers and risk stratification to predict hepatocellular cancer by Katrina Li, Brandon Mathew, Ethan Saldanha, Puja Ghosh, Adrian R. Krainer, Srinivasan Dasarathy, Hai Huang, Xiyan Xiang, Lopa Mishra

“…Abstract Hepatocellular carcinoma (HCC) is the third major cause of cancer death worldwide, with more than a doubling of incidence over the past two decades in the United States. …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. Background: The standard diagnostic criteria tools for FH require GT. …”
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PRKDC regulates cGAMP to enhance immune response in lung cancer treatment by Zhanghao Huang, Zhanghao Huang, Zhanghao Huang, Runqi Huang, Runqi Huang, Runqi Huang, Jun Zhu, Jun Zhu, Youlang Zhou, Youlang Zhou, Jiahai Shi, Jiahai Shi

“…This study aimed to investigate the antitumor effects of 2’,3’-cGAMP in LUAD.MethodHerein, patients with LUAD were screened for prognostic biomarkers, which were then assessed for sensitivity to immunotherapy and chemotherapy utilizing the “TIDE” algorithm and CellMiner database. …”
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Association between the development of sepsis and the triglyceride-glucose index in acute pancreatitis patients: a retrospective investigation utilizing the MIMIC-IV database by Lin Xu, Xuejing Li, Na Zhang, Chunmei Guo, Pan Wang, Min Gao, Yanhui Zhang, Lixin Zhao

“…Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
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Leveraging advanced technologies for early detection and diagnosis of oral cancer: Warning alarm by Saantosh Saravanan, N. Aravindha Babu, Lakshmi T, Mukesh Kumar Dharmalingam Jothinathan

“…Specialized algorithms such as the Recombination-Based Improved Population Optimization Parallel Covariance Matrix Adaptation Evolution Strategy (RB-IPOP CMA-ES) allow for better accuracy of deep learning models, as this enhances the performance of developing models for early diagnosis of oral cancer. …”
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Prognostic and Diagnostic Value of Spontaneous Tumor-Related Antibodies by Sebastian Kobold, Tim Luetkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic

“…There is an urgent need for earlier diagnosis of malignancies and more stringent monitoring of relapses after antitumor therapy. …”
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EEG Signal Analysis for Numerical Digit Classification: Methodologies and Challenges by Augoustos Tsamourgelis, Adam Adamopoulos

“…We achieve strong differentiation capabilities between digit and non-digit values in all classification algorithms. However, our study also highlights the profound neurological challenges encountered in distinguishing between the digit values, as our model, inspired by the related bibliography, was unable to differentiate between digit values 0 and 1. …”
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