Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

MLNI is a python package that performs various tasks using neuroimaging data: i) binary classification for disease diagnosis, following good practice proposed in AD-ML; ii) regression prediction, such ...

Abstract: This study evaluates metrics for tasks such as classification, regression, clustering, correlation analysis, statistical tests, segmentation, and image-to-image (I2I) translation in medical ...

Optical neural networks implemented with Mach-Zehnder Interferometer (MZI) arrays are a promising solution to enable fast and energy-efficient machine learning inference, yet finding a practical ...

Abstract: This paper presents a novel approach to binary classification using dynamic logistic ensemble models. The proposed method addresses the challenges posed by datasets containing inherent ...

Control flow graphs (CFGs) and function call graphs (FCGs) have become pivotal in providing a detailed understanding of program execution and effectively characterizing the behaviour of malware. These ...