Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Machine learning techniques for the diagnosis of Alzheimer's disease: A review
Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …
elderly population. Efficient automated techniques are needed for early diagnosis of …
A comprehensive analysis of nature-inspired meta-heuristic techniques for feature selection problem
M Sharma, P Kaur - Archives of Computational Methods in Engineering, 2021 - Springer
Meta-heuristics are problem-independent optimization techniques which provide an optimal
solution by exploring and exploiting the entire search space iteratively. These techniques …
solution by exploring and exploiting the entire search space iteratively. These techniques …
A review of feature reduction techniques in neuroimaging
B Mwangi, TS Tian, JC Soares - Neuroinformatics, 2014 - Springer
Abstract Machine learning techniques are increasingly being used in making relevant
predictions and inferences on individual subjects neuroimaging scan data. Previous studies …
predictions and inferences on individual subjects neuroimaging scan data. Previous studies …
Diagnosis of chronic kidney disease based on support vector machine by feature selection methods
Abstract As Chronic Kidney Disease progresses slowly, early detection and effective
treatment are the only cure to reduce the mortality rate. Machine learning techniques are …
treatment are the only cure to reduce the mortality rate. Machine learning techniques are …
Identifying autism spectrum disorder from resting-state fMRI using deep belief network
With the increasing prevalence of autism spectrum disorder (ASD), it is important to identify
ASD patients for effective treatment and intervention, especially in early childhood …
ASD patients for effective treatment and intervention, especially in early childhood …
[HTML][HTML] Exploring innovation ecosystems across science, technology, and business: A case of 3D printing in China
G Xu, Y Wu, T Minshall, Y Zhou - Technological Forecasting and Social …, 2018 - Elsevier
The concept of the innovation ecosystem is receiving increasing attention worldwide.
Governments and industrialists are keen to foster innovation ecosystems to systematically …
Governments and industrialists are keen to foster innovation ecosystems to systematically …
Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature …
We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …
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 …
[HTML][HTML] An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease
Voxel-based morphometry from conventional T1-weighted images has proved effective to
quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate …
quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate …