SVM-based multimodal classification of activities of daily living in health smart homes: sensors, algorithms, and first experimental results
By 2050, about one third of the French population will be over 65. Our laboratory's current
research focuses on the monitoring of elderly people at home, to detect a loss of autonomy …
research focuses on the monitoring of elderly people at home, to detect a loss of autonomy …
[图书][B] Kernel based algorithms for mining huge data sets
This is a book about (machine) learning from (experimental) data. Many books devoted to
this broad field have been published recently. One even feels tempted to begin the previous …
this broad field have been published recently. One even feels tempted to begin the previous …
Cardiac sound murmurs classification with autoregressive spectral analysis and multi-support vector machine technique
S Choi, Z Jiang - Computers in biology and medicine, 2010 - Elsevier
In this paper, a novel cardiac sound spectral analysis method using the normalized
autoregressive power spectral density (NAR-PSD) curve with the support vector machine …
autoregressive power spectral density (NAR-PSD) curve with the support vector machine …
Network-based identification of biomarkers coexpressed with multiple pathways
Unraveling complex molecular interactions and networks and incorporating clinical
information in modeling will present a paradigm shift in molecular medicine. Embedding …
information in modeling will present a paradigm shift in molecular medicine. Embedding …
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background Classification studies using gene expression datasets are usually based on
small numbers of samples and tens of thousands of genes. The selection of those genes that …
small numbers of samples and tens of thousands of genes. The selection of those genes that …
Textural pattern classification for oral squamous cell carcinoma
Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains
to be widely researched. Studies on computer‐aided analysis of pathological slides of oral …
to be widely researched. Studies on computer‐aided analysis of pathological slides of oral …
Investigating the efficacy of nonlinear dimensionality reduction schemes in classifying gene and protein expression studies
G Lee, C Rodriguez… - IEEE/ACM Transactions on …, 2008 - ieeexplore.ieee.org
The recent explosion in procurement and availability of high-dimensional gene and protein
expression profile data sets for cancer diagnostics has necessitated the development of …
expression profile data sets for cancer diagnostics has necessitated the development of …
Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms
The need to minimize the potential impact of air pollutants on humans has made the
accurate prediction of concentrations of air pollutants a crucial subject in environmental …
accurate prediction of concentrations of air pollutants a crucial subject in environmental …
A gene selection method for microarray data based on binary PSO encoding gene-to-class sensitivity information
F Han, C Yang, YQ Wu, JS Zhu, QH Ling… - … ACM transactions on …, 2015 - ieeexplore.ieee.org
Traditional gene selection methods for microarray data mainly considered the features'
relevance by evaluating their utility for achieving accurate predication or exploiting data …
relevance by evaluating their utility for achieving accurate predication or exploiting data …
[HTML][HTML] Development and multicenter validation of a CT-based radiomics signature for discriminating histological grades of pancreatic ductal adenocarcinoma
N Chang, L Cui, Y Luo, Z Chang, B Yu… - Quantitative imaging in …, 2020 - ncbi.nlm.nih.gov
Background The histological grade of pancreatic cancer is an important independent
predictor of outcome. However, we lack a method for safely and accurately obtaining the …
predictor of outcome. However, we lack a method for safely and accurately obtaining the …