[HTML][HTML] Developments, application, and performance of artificial intelligence in dentistry–A systematic review

SB Khanagar, A Al-Ehaideb, PC Maganur… - Journal of dental …, 2021 - Elsevier
Background/purpose Artificial intelligence (AI) has made deep inroads into dentistry in the
last few years. The aim of this systematic review was to identify the development of AI …

Novel machine learning applications on fly ash based concrete: an overview

G Khambra, P Shukla - Materials Today: Proceedings, 2023 - Elsevier
A machine learning technique provides rapid access to various information models,
approaches, complex systems, and algorithms. In the present scenario the artificial neural …

Extended dissipative state estimation for Markov jump neural networks with unreliable links

H Shen, Y Zhu, L Zhang, JH Park - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
This paper is concerned with the problem of extended dissipativity-based state estimation for
discrete-time Markov jump neural networks (NNs), where the variation of the piecewise time …

An overview of deep learning in the field of dentistry

JJ Hwang, YH Jung, BH Cho… - Imaging science in …, 2019 - synapse.koreamed.org
Purpose Artificial intelligence (AI), represented by deep learning, can be used for real-life
problems and is applied across all sectors of society including medical and dental field. The …

Multi‐scale Internet traffic forecasting using neural networks and time series methods

P Cortez, M Rio, M Rocha, P Sousa - Expert Systems, 2012 - Wiley Online Library
This article presents three methods to forecast accurately the amount of traffic in TCP/IP
based networks: a novel neural network ensemble approach and two important adapted …

Artificial neural network development by means of a novel combination of grammatical evolution and genetic algorithm

F Ahmadizar, K Soltanian, F AkhlaghianTab… - … Applications of Artificial …, 2015 - Elsevier
The most important problems with exploiting artificial neural networks (ANNs) are to design
the network topology, which usually requires an excessive amount of expert's effort, and to …

ANN model for predicting the compressive strength of circular steel-confined concrete

M Ahmadi, H Naderpour, A Kheyroddin - International Journal of Civil …, 2017 - Springer
Concrete filled steel tube is constructed using various tube shapes to obtain most efficient
properties of concrete core and steel tube. The compressive strength of concrete is …

[HTML][HTML] Application of machine learning in rheumatic disease research

KJ Kim, I Tagkopoulos - The Korean journal of internal medicine, 2019 - ncbi.nlm.nih.gov
Over the past decade, there has been a paradigm shift in how clinical data are collected,
processed and utilized. Machine learning and artificial intelligence, fueled by breakthroughs …

Crude oil price analysis and forecasting using wavelet decomposed ensemble model

K He, L Yu, KK Lai - Energy, 2012 - Elsevier
To improve the forecasting accuracy of crude oil price with deeper understanding of the
market microstructure, this paper proposes a wavelet decomposed ensemble model. The …

Rosette tracker: an open source image analysis tool for automatic quantification of genotype effects

J De Vylder, F Vandenbussche, Y Hu, W Philips… - Plant …, 2012 - academic.oup.com
Abstract Image analysis of Arabidopsis (Arabidopsis thaliana) rosettes is an important
nondestructive method for studying plant growth. Some work on automatic rosette …