Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Objective: To develop and validate a machine learning (ML)-based prediction model of Bethesda III nodules and create a nomogram based on the best model. Methods: We collected data on patients with ...
Abstract: To compare the accuracy of the Random Forest algorithm with the Novel Logistic Regression Technique in order to predict the data quality issues for the voice emotion identification system.
Introduction: Retirement is one of the most significant status changes in an individual's later life. Physical health and cognitive ability are key predictors of retirement adjustment. However, ...
Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Background This study aimed to develop and validate a hybrid model integrating clinical features, vessel wall magnetic resonance imaging (VWMRI) characteristics, and radiomic features to predict the ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...
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 ...
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