Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Researchers mapped 442,239 single nuclei from nonfailing human hearts to chart how cardiac cells change from fetal ...
Abstract: With the rapid growth of Internet data volumes, Big Data analysis technologies have gradually permeated all aspects of life. However, the existence of data silos and the promulgation of ...
Abstract: Breast cancer is as one of the common and serious cause of death among women globally. This is a disease where the cells grow out of control inside the breast. Family History of cancer ...
Bacteriophages, which infect bacterial cells, have a unique ability to reduce bacterial colonization, particularly in antibiotic-resistant biofilm infections. This study aims to fabricate optimized ...
LR was chosen as the best algorithm for model construction, and the model demonstrated excellent performance, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.866, a ...
1 Microbiome Research Group, Research Centre for Life Science and Healthcare, Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute (CBI), University of Nottingham Ningbo ...
Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation. Methods From the SCOT-HEART ...
Pharmacometrics represents a strategy to optimize and rationalize decision-making process integrating information on drug behavior, pharmacological response, and disease progression both in the drug ...
Six machine learning algorithms—k-nearest neighbors, naive Bayes, multilayer perceptron, random forest, support vector machine, and Extreme Gradient Boosting (XGBoost)—were developed using 10-fold ...
This project builds a fraud detection system using Gradient Boosting and XGBoost on 200,000+ real credit card transactions. The core challenge is extreme class imbalance — only 0.25% of transactions ...
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