Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…These findings highlight the potential of TinyML to provide accessible, reliable, and real-time diagnostic tools, particularly in remote and underserved areas, demonstrating the transformative impact of integrating advanced AI algorithms into portable medical devices. This advancement facilitates the prospect of automated respiratory health screening using lung sounds.…”
Get full text

DEVELOPMENT OF SOFTWARE SYSTEM FOR MONITORING OF STRESS CORROSION CRACKING OF THE PIPELINE UNDER TENSION by Z. K. Abaev, B. A. Bachiev

“…The working algorithm of developed program and the screen forms are presented.…”
Get full text

Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation. by Katherine I Morley, Joshua Wallace, Spiros C Denaxas, Ross J Hunter, Riyaz S Patel, Pablo Perel, Anoop D Shah, Adam D Timmis, Richard J Schilling, Harry Hemingway

“…<h4>Results</h4>The phenotype algorithm incorporated 286 codes: 201 Read, 63 BNF, 18 ICD-10, and four OPCS-4. …”
Get full text

Joint analysis of single-cell RNA sequencing and bulk transcriptome reveals the heterogeneity of the urea cycle of astrocytes in glioblastoma by Minfeng Tong, Qi Tu, Lude Wang, Huahui Chen, Xing Wan, Zhijian Xu

“…For bulk RNA-seq, univariate Cox and LASSO analyses were undertaken to screen prognostic genes, while multivariate Cox regression analysis was applied to set up a prognostic model. …”
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

Adaptive Feature Selection of Unbalanced Data for Skiing Teaching by Tao Feng

“…If the features are not selected, the model may overly rely on the features of common actions and ignore the features of difficult actions. …”
Get full text

Identification of retinol dehydrogenase 10 as a shared biomarker for metabolic dysfunction-associated steatotic liver disease and type 2 diabetes mellitus by Fangyu Li, Rui Li, Hongjun Deng

“…The LASSO algorithm and ROC curve identified Retinol Dehydrogenase 10 (RDH10) as the best diagnostic gene for MASLD and T2DM. …”
Get full text

Integrative multi-omics analysis reveals the role of toll-like receptor signaling in pancreatic cancer by Jie Peng, Jiaao Sun, Youfeng Yu, Qihang Yuan, Yong Zhang

“…In the process of building prognostic models, we screened 33 core genes related to the prognosis of pancreatic cancer, and combined a series of machine learning algorithms to build the prognosis model of pancreatic cancer. …”
Get full text

Artificial Intelligence in Pediatric Blood Transfusion during Anesthesia: A Scoping Review by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, Maryam Aligholizadeh, Siavash Sangi

“…Relevant keywords, including artificial intelligence, machine learning, predictive model, neural network, predictive algorithm, blood transfusion, children, pediatric, neonates, anesthesia, surgery, and operation, were extracted from the Medical Subject Headings (MeSH). …”
Get full text

Few-Shot Intelligent Anti-Jamming Access with Fast Convergence: A GAN-Enhanced Deep Reinforcement Learning Approach by Tianxiao Wang, Yingtao Niu, Zhanyang Zhou

“…The method constructs a Generative Adversarial Network (GAN) to learn the time–frequency distribution characteristics of short-period jamming and to generate high-fidelity mixed samples. Furthermore, it screens qualified samples using the Pearson correlation coefficient to form a sample set, which is input into the DQN network model for pre-training to expand the experience replay buffer, effectively improving the convergence speed and decision accuracy of DQN. …”
Get full text

Application of Data Mining Technology on Surveillance Report Data of HIV/AIDS High-Risk Group in Urumqi from 2009 to 2015 by Dandan Tang, Man Zhang, Jiabo Xu, Xueliang Zhang, Fang Yang, Huling Li, Li Feng, Kai Wang, Yujian Zheng

“…The goal of this study was to use four data mining algorithms to establish the identification model of HIV infection and compare their predictive performance. …”
Get full text

Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
Get full text

The impact of specialised gastroenterology services for pelvic radiation disease (PRD): Results from the prospective multi-centre EAGLE study. by John N Staffurth, Stephanie Sivell, Elin Baddeley, Sam Ahmedzai, H Jervoise Andreyev, Susan Campbell, Damian J J Farnell, Catherine Ferguson, John Green, Ann Muls, Raymond O'Shea, Sara Pickett, Lesley Smith, Sophia Taylor, Annmarie Nelson

“…All men completed a validated screening tool for late bowel effects (ALERT-B) and the Gastrointestinal Symptom Rating Score (GSRS); men with a positive score on ALERT-B were offered management following a peer reviewed algorithm for pelvic radiation disease (PRD). …”
Get full text

Research on Feature Extraction of Performance Degradation for Flexible Material R2R Processing Roller Based on PCA by Yaohua Deng, Huiqiao Zhou, Kexing Yao, Zhiqi Huang, Chengwang Guo

“…The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. …”
Get full text

A machine learning approach to predict positive coronary artery calcium scores in individuals with diabetes: a cross-sectional analysis of ELSA-Brasil baseline data by J.L. Amorim, I.M. Bensenor, A.P. Alencar, A.C. Pereira, A.C. Goulart, P.A. Lotufo, I.S. Santos

“…We analyzed 25 sociodemographic, medical history, symptom-related, and laboratory variables from 585 participants from the São Paulo investigation center with CACS data and no overt cardiovascular disease at baseline. We used six ML algorithms to build models to identify individuals with positive CACS. …”
Get full text

GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Subsequently, a two-stage suppression model based on robust estimation theory is developed to effectively suppress interference. …”
Get full text

Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…In addition, image data using more variables as model inputs, including agriculture sensors and meteorological data, have increased prediction accuracy. …”
Get full text

Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review by Tianyi Liu, Andrew J. Krentz, Zhiqiang Huo, Vasa Ćurčin

“…The synthesis underscores the superiority of ML in modeling intricate EHR-derived risk factors, facilitating precision-driven cardiovascular risk assessment. …”
Get full text

Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications by Can Qi, Can Qi, Ziwei Zhao, Lin Chen, Le Wang, Yun Zhou, Guochen Duan, Guochen Duan

“…A total of five biomarkers,[Selenoprotein P1 (SEPP1), Fibrinogen-like protein 2 (FGL2), NK cell lectin-like receptor K1 (KLRK1), ATP-binding cassette transporters 6(ABCA6) and Galectins(GAL)], were screened, and a risk model based on the biomarkers was created. …”
Get full text

Automated machine learning for predicting perioperative ischemia stroke in endovascularly treated ruptured intracranial aneurysm patients by Yuhang Peng, Ke Bi, Xiaolin Zhang, Ning Huang, Xiang Ji, Weifu Chen, Ying Ma, Yuan Cheng, Yongxiang Jiang, Jianhe Yue

“…The least absolute shrinkage and selection operator (LASSO) method was used to screen essential features associated with PIS. Based on these features, nine machine learning models were constructed using a training set (75% of participants) and assessed on a test set (25% of participants). …”
Get full text