AIMC Topic: Algorithms

Clear Filters Showing 20161 to 20170 of 28713 articles

A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network.

International journal of biological sciences
In this paper, a method of characteristic extraction and recognition on lung sounds is given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by...

State-of-the-art review on deep learning in medical imaging.

Frontiers in bioscience (Landmark edition)
Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought...

MITK Phenotyping: An open-source toolchain for image-based personalized medicine with radiomics.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Radiomics - The extraction of quantitative features from radiologic images - shows increasing potential in contributing to modern personalized medicine approaches. MITK Phenotyping is an openly distributed radiomics framework implementing an exhausti...

Segmenting lung tumors on longitudinal imaging studies via a patient-specific adaptive convolutional neural network.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To design a deep learning algorithm that automatically delineates lung tumors seen on weekly magnetic resonance imaging (MRI) scans acquired during radiotherapy and facilitates the analysis of geometric tumor changes.

CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features.

BMC medical genomics
BACKGROUND: Long noncoding RNAs (lncRNAs) are widely involved in the initiation and development of cancer. Although some computational methods have been proposed to identify cancer-related lncRNAs, there is still a demanding to improve the prediction...

miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase.

BMC bioinformatics
BACKGROUND: miRBase is the primary repository for published miRNA sequence and annotation data, and serves as the "go-to" place for miRNA research. However, the definition and annotation of miRNAs have been changed significantly across different vers...

PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.

BMC bioinformatics
BACKGROUND: Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-binding residue prediction approach...

Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs.

BMC bioinformatics
BACKGROUND: Distinction between pre-microRNAs (precursor microRNAs) and length-similar pseudo pre-microRNAs can reveal more about the regulatory mechanism of RNA biological processes. Machine learning techniques have been widely applied to deal with ...

Ultrasonic Tethering to Enable Side-by-Side Following for Powered Wheelchairs.

Sensors (Basel, Switzerland)
In social situations, people who use a powered wheelchair must divide their attention between navigating the chair and conversing with people. These conversations could lead to increased mental stress when navigating and distraction from maneuvering ...

Prediction of fatty liver disease using machine learning algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for preven...