In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
Using machine learning methods to predict post-traumatic stress disorder in stroke patients in China
Background: This study aims to utilize various machine learning algorithms to construct a risk prediction model for post-stroke Post-Traumatic Stress Disorder (PTSD), select the optimal model, and ...
Designed to accelerate advances in medicine and other fields, the tech giant’s quantum algorithm runs 13,000 times as fast as software written for a traditional supercomputer. A quantum computer at ...
Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...
SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...
Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
The 2018 General Education Program in Vietnam emphasizes personalized learning and the application of technology in teaching. This study proposes a customized learning system integrating artificial ...
Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback