Association between age and lung cancer risk: evidence from lung lobar radiomics by Yuwei Li, Chengting Lin, Lei Cui, Chao Huang, Liting Shi, Shiyang Huang, Yue Yu, Xianglan Zhou, Qian Zhou, Kun Chen, Lei Shi

“…The minimum redundancy maximum relevance algorithm was applied to identify the top 10 age-related radiomic features among 13,137 never smokers. …”
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Bidirectional Relationship Between Hypoalbuminemia and Postoperative Pneumonia in Elderly Hip Fracture Patients: A Retrospective Cohort Study by Wang J, Yu H, Xu X, Guo J

“…After predefined participants selection inclusion and exclusion criteria, 1661 surgically treated HF patients were included and analyzed utilizing multiple statistical models, including univariate logistic regression, Lasso regression, and Boruta algorithm for variable selection, while multivariate logistic regression and propensity score matching (PSM) for assess the bidirectional relationship between hypoalbuminemia and postoperative pneumonia. …”
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Identification and validation of ubiquitination-related genes for predicting cervical cancer outcome by Ge Jin, Xiaomei Fan, Xiaoliang Liang, Honghong Dai, Jun Wang

“…The risk score model constructed based on these biomarkers could effectively predict the survival rate of cervical cancer patients (AUC >0.6 for 1/3/5 years). …”
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Registered report protocol: A scoping review to identify potential predictors as features for developing automated estimation of the probability of being frail in secondary care. by Dirk H van Dalen, Angèle P M Kerckhoffs, Esther de Vries

“…We aim to identify potential predictors that could be used as features for modeling algorithms on the basis of routine hospital EHR data to incorporate in an automated tool for estimating the probability of being frail.…”
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Canadian Thoracic Society Recommendations for Management of Chronic Obstructive Pulmonary Disease – 2008 Update – Highlights for Primary Care by Denis E O’Donnell, Paul Hernandez, Alan Kaplan, Shawn Aaron, Jean Bourbeau, Darcy Marciniuk, Meyer Balter, Gordon Ford, Andre Gervais, Yves Lacasse, Francois Maltais, Jeremy Road, Graeme Rocker, Don Sin, Tasmin Sinuff, Nha Voduc

“…Three key messages contained in the update are: use targeted screening spirometry to establish a diagnosis and initiate prompt management (including smoking cessation) of mild COPD; improve dyspnea and activity limitation in stable COPD using new evidence-based treatment algorithms; and understand the importance of preventing and managing acute exacerbations, particularly in moderate to severe disease.…”
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Machine learning approach effectively discriminates between Parkinson’s disease and progressive supranuclear palsy: Multi-level indices of rs-fMRI by Weiling Cheng, Xiao Liang, Wei Zeng, Jiali Guo, Zhibiao Yin, Jiankun Dai, Daojun Hong, Fuqing Zhou, Fangjun Li, Xin Fang

“…Various rs-fMRI indices were extracted, followed by a comprehensive feature screening for each index. We constructed fifteen distinct combinations of indices and selected four machine learning algorithms for model development. …”
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Design and validation of a novel multiple sites signal acquisition and analysis system based on pressure stimulation for human cardiovascular information by Gaiqin Liu, Yuan Li, Longcong Chen, Juan Jiang, Jie Tian, Panpan Feng

“…Furthermore, the results suggest that the system can facilitate in-depth research into the relationships between collected signals and CVDs, provide rich raw data for cardiovascular health assessment and disease prediction models based on machine learning algorithms, and offer a new non-invasive method for early diagnosis, evaluation, and prediction of CVDs.…”
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Prevalence of tuberculosis, HIV and respiratory symptoms in two Zambian communities: implications for tuberculosis control in the era of HIV. by Helen Ayles, Albertus Schaap, Amos Nota, Charalambos Sismanidis, Ruth Tembwe, Petra De Haas, Monde Muyoyeta, Nulda Beyers, Peter Godfrey-Faussett for the ZAMSTAR Study Team

“…Epidemiological studies can inform screening algorithms for both detection and prevention of active tuberculosis.…”
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Lesion classification and diabetic retinopathy grading by integrating softmax and pooling operators into vision transformer by Chong Liu, Weiguang Wang, Jian Lian, Wanzhen Jiao

“…Therefore, plenty of automated screening technique have been developed to address this task.MethodsAmong these techniques, the deep learning models have demonstrated promising outcomes in various types of machine vision tasks. …”
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Development and validation of a nomogram for predicting in-hospital mortality in older adult hip fracture patients with atrial fibrillation: a retrospective study by Zhenli Li, Jing He, Tiezhu Yao, Guang Liu, Jing Liu, Ling Guo, Mengjia Li, Mengjia Li, Zhengkun Guan, Zhengkun Guan, Ruolian Gao, Jingtao Ma

“…Logistic regression (LR) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were employed to screen features. We further used Extreme Gradient Boosting (XGBoost) based on features selected by LR and LASSO algorithms to assist in identifying the final model-established features. …”
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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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RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

“…In this study, the combined roles of m7G methylation regulators were explored in COPD for the first time by integrated bioinformatic methods. The machine algorithms screened 7 disease signature genes relevant to clinical indicators, including CYFIP2, EIF3D, EIF4G3, GEMIN5, METTL1, SNUPN and NCBP2, and METTL1 was related to the progression in COPD. …”
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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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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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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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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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Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification by Miao Yu, Zhenqi Ye, Zixin Ye, Yaping Wu, Xiang Wu

“…Then, machine learning algorithms were exploited to screen hub NRGs, and a predictive model was constructed based on these hub NRGs. …”
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How math shapes the world of life science animation by Rafael Oliveira, Evellyn Araujo Dias, Evellyn Araujo Dias, Ricardo Santos, Ricardo Santos, Vinicius Cotta-De-Almeida, José Aguiar Coelho Nt, José Aguiar Coelho Nt, José Aguiar Coelho Nt, Luiz Anastácio Alves

“…This paper elucidates the role of matrix manipulation in animating figures on screens, elucidates the distinctions between Scalable Vector Graphics (SVG), bitmap and raster images, and unveils the inner workings of the Bresenham algorithm in the context of rendering lines on screens. …”
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Exploring ischemic stroke based on the ferroptosis perspective: ECH1 may serve as a new biomarker and therapeutic target by Rendong Qu, Yiyan Zhang, Haojia Zhang, Ke Li, Boning Zhang, Hongxuan Tong, Tao Lu

“…Using differential expression analysis and machine learning algorithms, 12 potential hub genes were successfully screened. …”
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