[HTML][HTML] Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI
Purpose We propose a fully automated method for detection and segmentation of the
abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid …
abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid …
Artificial intelligence and internet of things in screening and management of autism spectrum disorder
Autism is a disability that obstructs the process of a person's development. Autistic
individuals find it extremely difficult to cope with the world's pace, can not communicate …
individuals find it extremely difficult to cope with the world's pace, can not communicate …
Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms
With the development of clinical technologies, different tumor features have been collected
for breast cancer diagnosis. Filtering all the pertinent feature information to support the …
for breast cancer diagnosis. Filtering all the pertinent feature information to support the …
[HTML][HTML] Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis
Q Pei, Y Luo, Y Chen, J Li, D Xie, T Ye - Clinical Chemistry and …, 2022 - degruyter.com
Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …
language recognition, image recognition, natural language processing, and expert systems …
[HTML][HTML] DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Abstract Background and Objective: Although automated Skin Lesion Classification (SLC) is
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
Human pluripotent stem cell-derived neural constructs for predicting neural toxicity
Human pluripotent stem cell-based in vitro models that reflect human physiology have the
potential to reduce the number of drug failures in clinical trials and offer a cost-effective …
potential to reduce the number of drug failures in clinical trials and offer a cost-effective …
Support vector machines used to estimate the battery state of charge
JCA Anton, PJG Nieto, CB Viejo… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
The aim of this study is to estimate the state of charge (SOC) of a high-capacity lithium iron
manganese phosphate (LiFeMnPO _4) battery cell from an experimental dataset using a …
manganese phosphate (LiFeMnPO _4) battery cell from an experimental dataset using a …
[PDF][PDF] An introduction to variable and feature selection
I Guyon, A Elisseeff - Journal of machine learning research, 2003 - jmlr.org
Variable and feature selection have become the focus of much research in areas of
application for which datasets with tens or hundreds of thousands of variables are available …
application for which datasets with tens or hundreds of thousands of variables are available …
[图书][B] Learning with kernels: support vector machines, regularization, optimization, and beyond
B Schölkopf, AJ Smola - 2002 - books.google.com
A comprehensive introduction to Support Vector Machines and related kernel methods. In
the 1990s, a new type of learning algorithm was developed, based on results from statistical …
the 1990s, a new type of learning algorithm was developed, based on results from statistical …
Gene selection for cancer classification using support vector machines
DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and
determine whether those genes are active, hyperactive or silent in normal or cancerous …
determine whether those genes are active, hyperactive or silent in normal or cancerous …