Abstract Machine learning (ML) is a burgeoning field of medicine with huge resources being
applied to fuse computer science and statistics to medical problems. Proponents of ML extol …

Computer technology has been advanced tremendously and the interest has been
increased for the potential use of 'Artificial Intelligence (AI)'in medicine and biological …

The use of complex numbers in neural networks is as natural as their use in other
engineering areas and in mathematics. The history of complex numbers shows that although …

White blood cell detection is one of the most basic and key steps in the automatic
recognition system of white blood cells in microscopic blood images. Its accuracy and …

Artificial neural networks are computational paradigms based on mathematical models that
unlike traditional computing have a structure and operation that resembles that of the …

Natural computing, through its repertoire of nature-inspired strategies, is playing a major role
in the development of intelligent decision-making systems. The objective is to provide …

We propose a supervised machine learning approach for boosting existing signal and
image recovery methods and demonstrate its efficacy on example of image reconstruction in …

Several efforts have been made to completely automate cephalometric analysis by
automatic landmark search. However, accuracy obtained was worse than manual …

This brief discusses a class of discrete-time recurrent neural networks with complex-valued
linear threshold neurons. It addresses the boundedness, global attractivity, and complete …

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-
enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast …