Computer-aided diagnosis: A survey with bibliometric analysis
R Takahashi, Y Kajikawa - International journal of medical informatics, 2017 - Elsevier
Computer-aided diagnosis (CAD) has been a promising area of research over the last two
decades. However, CAD is a very complicated subject because it involves a number of …
decades. However, CAD is a very complicated subject because it involves a number of …
Early diagnosis of Alzheimer׳ s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images
Computer aided diagnosis (CAD) systems using functional and structural imaging
techniques enable physicians to detect early stages of the Alzheimer׳ s disease (AD). For …
techniques enable physicians to detect early stages of the Alzheimer׳ s disease (AD). For …
Early diagnosis of Alzheimer's disease based on resting-state brain networks and deep learning
Computerized healthcare has undergone rapid development thanks to the advances in
medical imaging and machine learning technologies. Especially, recent progress on deep …
medical imaging and machine learning technologies. Especially, recent progress on deep …
Smart Gas Sensors: Materials, Technologies, Practical Applications, and Use of Machine Learning–A Review
The electronic nose, popularly known as the E-nose, that combines gas sensor arrays
(GSAs) with machine learning has gained a strong foothold in gas sensing technology. The …
(GSAs) with machine learning has gained a strong foothold in gas sensing technology. The …
Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree
In this paper we proposed a novel classification system to distinguish among elderly
subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal …
subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal …
A non-parametric statistical inference framework for deep learning in current neuroimaging
Deep Learning (DL) predictions are uncertain; but how uncertain? Statistical inference
estimates the probabilities of uncertainty from a sample drawn from a population. Assessing …
estimates the probabilities of uncertainty from a sample drawn from a population. Assessing …
NMF-SVM based CAD tool applied to functional brain images for the diagnosis of Alzheimer's disease
This paper presents a novel computer-aided diagnosis (CAD) technique for the early
diagnosis of the Alzheimer's disease (AD) based on nonnegative matrix factorization (NMF) …
diagnosis of the Alzheimer's disease (AD) based on nonnegative matrix factorization (NMF) …
Microarray medical data classification using kernel ridge regression and modified cat swarm optimization based gene selection system
Microarray gene expression based medical data classification has remained as one of the
most challenging research areas in the field of bioinformatics, machine learning and pattern …
most challenging research areas in the field of bioinformatics, machine learning and pattern …
Performance of machine learning methods applied to structural MRI and ADAS cognitive scores in diagnosing Alzheimer's disease
Early detection of Alzheimer's disease (AD) using structural magnetic resonance images is
essential for early treatment that can slow the progression of the disease. Therefore, there is …
essential for early treatment that can slow the progression of the disease. Therefore, there is …
A CNN–RNN–LSTM based amalgamation for Alzheimer's disease detection
M Dua, D Makhija, PYL Manasa, P Mishra - Journal of Medical and …, 2020 - Springer
Purpose Alzheimer's disease is a fatal brain condition that causes irreversible brain damage
and gradually depletes memory of an individual. The basic idea of the presented work in this …
and gradually depletes memory of an individual. The basic idea of the presented work in this …