eD octor: machine learning and the future of medicine
GS Handelman, HK Kok, RV Chandra… - Journal of internal …, 2018 - Wiley Online Library
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 …
applied to fuse computer science and statistics to medical problems. Proponents of ML extol …
Applications of artificial neural networks in medical science
Computer technology has been advanced tremendously and the interest has been
increased for the potential use of 'Artificial Intelligence (AI)'in medicine and biological …
increased for the potential use of 'Artificial Intelligence (AI)'in medicine and biological …
[图书][B] Complex-valued neural networks with multi-valued neurons
I Aizenberg - 2011 - Springer
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 …
engineering areas and in mathematics. The history of complex numbers shows that although …
A new detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection
W Shitong, W Min - IEEE Transactions on information …, 2006 - ieeexplore.ieee.org
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 …
recognition system of white blood cells in microscopic blood images. Its accuracy and …
[PDF][PDF] Introduction to neural networks in healthcare
M Sordo - Open clinical: Knowledge management for medical …, 2002 - researchgate.net
Artificial neural networks are computational paradigms based on mathematical models that
unlike traditional computing have a structure and operation that resembles that of the …
unlike traditional computing have a structure and operation that resembles that of the …
Medical image analysis for cancer management in natural computing framework
S Mitra, BU Shankar - Information Sciences, 2015 - Elsevier
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 …
in the development of intelligent decision-making systems. The objective is to provide …
Spatially-adaptive reconstruction in computed tomography using neural networks
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 …
image recovery methods and demonstrate its efficacy on example of image reconstruction in …
An evaluation of cellular neural networks for the automatic identification of cephalometric landmarks on digital images
R Leonardi, D Giordano… - BioMed Research …, 2009 - Wiley Online Library
Several efforts have been made to completely automate cephalometric analysis by
automatic landmark search. However, accuracy obtained was worse than manual …
automatic landmark search. However, accuracy obtained was worse than manual …
Discrete-time recurrent neural networks with complex-valued linear threshold neurons
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 …
linear threshold neurons. It addresses the boundedness, global attractivity, and complete …
Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching
A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-
enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast …
enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast …