CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

This project reproduced the core functionalities of the auton-survival package, a comprehensive toolkit for survival analysis with censored time-to-event data. The reproduction validated 15 key ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...

Background: Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is one most frequent and severe complication of ERCP. In consideration of recent advancements in both ...

Abstract: Independent component regression (ICR) has become as an important spectroscopic calibration modeling method, due to its advantages in extracting non-Gaussian and high-order statistic ...

Objective: To develop a deep learning (DL) model for carotid plaque detection based on CTA images and evaluate the clinical application feasibility and value of the model. Methods: We retrospectively ...

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the ...