Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data by Erli Wu, Xuan Yin, Feng Liang, Xianqing Zhou, Jiamin Hu, Wanting Yuan, Feihan Gu, Jingxin Zhao, Ziyang Gao, Ming Cheng, Shouxiang Yang, Lei Zhang, Qingqing Wang, Qingqing Wang, Xiaoyu Sun, Xiaoyu Sun, Wei Shao, Wei Shao

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”
Get full text

Deep Multi-Modal Skin-Imaging-Based Information-Switching Network for Skin Lesion Recognition by Yingzhe Yu, Huiqiong Jia, Li Zhang, Suling Xu, Xiaoxia Zhu, Jiucun Wang, Fangfang Wang, Lianyi Han, Haoqiang Jiang, Qiongyan Zhou, Chao Xin

“…The diagnostic potential of recent multi-modal skin lesion detection algorithms is limited because they ignore dynamic interactions and information sharing across modalities at various feature scales. …”
Get full text

Risk factors and prediction model of breast cancer-related lymphoedema in a Chinese cancer centre: a prospective cohort study protocol by Yue Wang, Xin Li, Ying Wang, Hongmei Zhao, Qian Lu, Yujie Zhou, Liyuan Zhang, Aomei Shen, Jingru Bian, Wanmin Qiang, Jingming Ye, Hongmeng Zhao, Yubei Huang, Zhongning Zhang, Peipei Wu

“…Traditional COX regression analysis and seven common survival analysis machine learning algorithms (COX, CARST, RSF, GBSM, XGBS, SSVM and SANN) will be employed for model construction and validation.Ethics and dissemination The study protocol was approved by the Biomedical Ethics Committee of Peking University (IRB00001052-21124) and the Research Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (bc2023013). …”
Get full text

Predicting the risk of heart failure after acute myocardial infarction using an interpretable machine learning model by Qingqing Lin, Qingqing Lin, Wenxiang Zhao, Wenxiang Zhao, Hailin Zhang, Hailin Zhang, Wenhao Chen, Sheng Lian, Qinyun Ruan, Qinyun Ruan, Zhaoyang Qu, Zhaoyang Qu, Yimin Lin, Yimin Lin, Dajun Chai, Dajun Chai, Dajun Chai, Dajun Chai, Xiaoyan Lin, Xiaoyan Lin, Xiaoyan Lin, Xiaoyan Lin

“…For developing a predictive model for HF risk in AMI patients, the least absolute shrinkage and selection operator (LASSO) Regression was used to feature selection, and four ML algorithms including Random Forest (RF), Extreme Gradient Boost (XGBoost), Support Vector Machine (SVM), and Logistic Regression (LR) were employed to develop the model on the training set. …”
Get full text

Improved early detection of wheat stripe rust through integration pigments and pigment-related spectral indices quantified from UAV hyperspectral imagery by Anting Guo, Wenjiang Huang, Binxiang Qian, Kun Wang, Huanjun Liu, Kehui Ren

“…The early detection model for wheat stripe rust was developed using these parameters and machine learning algorithms. The results indicated selected pigments and SIs effectively distinguished stripe rust-infected wheat from healthy wheat at 7, 16, and 23 DPI. …”
Get full text

Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization by Yuan Liu, Yuan Liu, Xin Yuan, Xin Yuan, Yu-Chan He, Yu-Chan He, Zhong-Hai Bi, Zhong-Hai Bi, Si-Yao Li, Si-Yao Li, Ye Li, Ye Li, Yan-Li Liu, Yan-Li Liu, Liu Miao, Liu Miao

“…Techniques employed included propensity score matching (PSM), logistic regression, lasso regression, and random forest algorithms (RF). Risk factors were assessed, and the sensitivity and specificity of the models were evaluated using receiver operating characteristic (ROC) curves. …”
Get full text

FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites by J. Lai, J. Lai, Y. Zhang, A. Wang, W. Fei, Y. Diao, R. Li, J. Wu

“…However, the variables and algorithms related to environmental limiting factors differ significantly across various LUE models, leading to high uncertainty in GPP estimation. …”
Get full text

Global trends in the use of artificial intelligence for urological tumor histopathology: A 20-year bibliometric analysis by Fazhong Dai, Yifeng He, Juan Duan, Kangjian Lin, Qian Lv, Zhongxiang Zhao, Yesong Zou, Jianhong Jiang, Zongtai Zheng, Xiaofu Qiu

“…Prioritizing standardized data protocols, fairness-aware algorithms, and dynamic regulatory guidelines will be essential to ensure equitable, reliable, and clinically actionable AI solutions, ultimately advancing precision oncology in urological malignancies.…”
Get full text

The effect of canine lingual attachments during maxillary arch distalization with clear aligner: a 4D finite element analysis and in vitro simulator study by Bochun Mao, Yajing Tian, Hanzhang Zhou, Yan Gu

“…Method A dual-methodological approach was employed: 1) A four-dimensional finite element model (4D FEM) incorporating automated staging simulation was developed, utilizing iterative computations for long-term tooth movement prediction and thermal expansion algorithms for CA morphology adaptation; 2) An electromechanical orthodontic simulator (OSIM) was implemented for in vitro validation. …”
Get full text

The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality by Matthew D. Solomon, MD, PhD, Alan S. Go, MD, Thomas Leong, MPH, Elisha Garcia, BS, Kathy Le, MPH, Femi Philip, MD, Edward McNulty, MD, Jacob Mishell, MD, Andrew N. Rassi, MD, David C. Lange, MD, Catherine Lee, PhD, Anthony DeMaria, MD, Rick Nishimura, MD, Andrew P. Ambrosy, MD

“…Methods: In this retrospective cohort study from a large, integrated health care system serving >4.5 M individuals, we applied validated natural language processing algorithms to echocardiogram reports to identify physician-assessed AS severity and potential AS-related symptoms (eg, chest pain, syncope, dyspnea, worsening heart failure) via diagnosis codes and natural language processing-applied physician notes. …”
Get full text

Use of artificial intelligence to support prehospital traumatic injury care: A scoping review by Jake Toy, Jonathan Warren, Kelsey Wilhelm, Brant Putnam, Denise Whitfield, Marianne Gausche‐Hill, Nichole Bosson, Ross Donaldson, Shira Schlesinger, Tabitha Cheng, Craig Goolsby

“…The majority used machine learning (88%) alone or in conjunction with DL or NLP, and the top three algorithms used were support vector machine, logistic regression, and random forest. …”
Get full text

Prognostic factors of disability progression in multiple sclerosis in real life: the OFSEP-high definition (OFSEP-HD) prospective cohort in France by Francis Guillemin, Jonathan Epstein, Pierre Labauge, Christine Lebrun-Frénay, Eric Thouvenot, Laurent Magy, Jerome De Sèze, Pierre Clavelou, Pierre Branger, Alain Créange, Elisabeth Maillart, Thibault Moreau, Hamza Achit, Bruno Stankoff, Emmanuelle Leray, Gilles Edan, Sandra Vukusic, Olivier Heinzlef, Aurélie Ruet, Yohann Foucher, Philippe Cabre, Olivier Casez, Guillaume Mathey, Jonathan Ciron, Eric Berger, Caroline Papeix, Helene Zephir, David Laplaud, Inès Doghri, Amélie Dos Santos, Romain Casey, Fabien Rollot

“…The marginal effectiveness and tolerability of treatments will be assessed. Stratified algorithms will be proposed for medical decision-making. …”
Get full text

Clinical-radiomics hybrid modeling outperforms conventional models: machine learning enhances stratification of adverse prognostic features in prostate cancer by Minghan Jiang, Minghan Jiang, Zeyang Miao, Run Xu, Mengyao Guo, Xuefeng Li, Guanwu Li, Peng Luo, Su Hu, Su Hu

“…LASSO regression selected optimal features, followed by model construction via five algorithms (logistic regression, decision tree, random forest, SVM, AdaBoost). …”
Get full text

Assessing sepsis-induced immunosuppression to predict positive blood cultures by Enrique Hernández-Jiménez, Enrique Hernández-Jiménez, Erika P. Plata-Menchaca, Erika P. Plata-Menchaca, Damaris Berbel, Damaris Berbel, Guillem López de Egea, Guillem López de Egea, Macarena Dastis-Arias, Laura García-Tejada, Fabrizio Sbraga, Pierre Malchair, Nadia García Muñoz, Alejandra Larrad Blasco, Eva Molina Ramírez, Xose Pérez Fernández, Joan Sabater Riera, Arnau Ulsamer

“…Although not widely accepted, several clinical and artificial intelligence-based algorithms have been recently developed to predict bacteremia. …”
Get full text

Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magn... by Zhe Min, Fernando J. Bianco, Qianye Yang, Wen Yan, Ziyi Shen, David Cohen, Rachael Rodell, Dean C. Barratt, Yipeng Hu

“…The ground‐truth (GT) perspective lesion‐level sensitivity and prediction‐perspective lesion‐level precision are reported, to quantify the ratios of true positive voxels being detected by algorithms over the number of voxels in the GT labelled regions and predicted regions. …”
Get full text

A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…We also define bottom-up parsing algorithms to recommend the suitable crowd prevention plan w.r.t. the crowd level. …”
Get full text

Petrological controls on the engineering properties of carbonate aggregates through a machine learning approach by Javid Hussain, Tehseen Zafar, Xiaodong Fu, Nafees Ali, Jian Chen, Fabrizio Frontalini, Jabir Hussain, Xiao Lina, George Kontakiotis, Olga Koumoutsakou

“…Among these, the Gradient Boosting model demonstrated superior predictive capability, overcoming both traditional regression methods and other machine learning algorithms as validated through the Taylor diagram and ranking system (i.e., r = 0.998, R² = 997, Root mean square error = 0.075, Variance Accounted For = 99.50%, Mean Absolute Percentage Error = 0.385%, Alpha 20 Index = 100, and performance index = 0.975). …”
Get full text

Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. Diagnostic models were subsequently constructed and validated. …”
Get full text

Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…These findings underscore the feasibility of accurately prediction of hens'AF through fitting appropriate algorithms for different laying periods, that supporting delicacy feeding management in farm.…”
Get full text

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. …”
Get full text