Abstract Machine learning (ML) is a computerized analytical technique that is being
increasingly employed in biomedicine. ML often provides an advantage over explicitly …

Nowadays Internet services have dramatically changed the way people interact with each
other and many of our daily activities are supported by those services. Statistical indicators …

This study evaluates and compares the performance of different machine learning
techniques on predicting the individuals at risk of developing hypertension, and who are …

Medical imaging has evolved from a pure visualization tool to representing a primary source
of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral …

Classification and regression are the major applications of machine learning algorithms
which are widely used to solve problems in numerous domains of engineering and …

Aim To evaluate the potential of the Support Vector Machine Regression model (SVM-RM)
and Multilayer Neural Network Ensemble model (MLNN-EM) to improve the intraocular lens …

Performance of 2D-SWE.GE for predicting different stages of liver fibrosis, using Transient
Elastography as the reference method Page 1 Med Ultrason 2017, Vol. 19, no. 2, 143-149 …

The expansion of teleworking and the digital transition movement have given companies
and workers great flexibility, albeit with significant organisational consequences. The recent …

Traditionally, the skin sensitization potential of chemicals has been assessed using animal
models. Due to growing ethical, political, and financial concerns, sustainable alternatives to …

Detection and diagnosis of marine engines faults are extremely important functions for the
optimized voyage of any sea-going vessel, as well as the safe conduct of navigation. Early …