AIMC Topic: Algorithms

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Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

Journal of molecular biology
Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitati...

Functional Annotation of Proteins Encoded by the Minimal Bacterial Genome Based on Secondary Structure Element Alignment.

Journal of proteome research
In synthetic biology, one of the key focuses is building a minimal artificial cell which can provide basic chassis for functional study. Recently, the J. Craig Venter Institute published the latest version of the minimal bacterial genome JCVI-syn3.0,...

Medical Image Fusion Based on Sparse Representation and PCNN in NSCT Domain.

Computational and mathematical methods in medicine
The clinical assistant diagnosis has a high requirement for the visual effect of medical images. However, the low frequency subband coefficients obtained by the NSCT decomposition are not sparse, which is not conducive to maintaining the details of t...

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PloS one
Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of ...

Computer-assisted liver graft steatosis assessment via learning-based texture analysis.

International journal of computer assisted radiology and surgery
PURPOSE: Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being ...

Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data.

The Journal of experimental biology
Accelerometers are becoming ever more important sensors in animal-attached technology, providing data that allow determination of body posture and movement and thereby helping to elucidate behaviour in animals that are difficult to observe. We sought...

3D Tooth Segmentation and Labeling Using Deep Convolutional Neural Networks.

IEEE transactions on visualization and computer graphics
In this paper, we present a novel approach for 3D dental model segmentation via deep Convolutional Neural Networks (CNNs). Traditional geometry-based methods tend to receive undesirable results due to the complex appearance of human teeth (e.g., miss...

A machine learning based approach to identify protected health information in Chinese clinical text.

International journal of medical informatics
BACKGROUND: With the increasing application of electronic health records (EHRs) in the world, protecting private information in clinical text has drawn extensive attention from healthcare providers to researchers. De-identification, the process of id...

Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

Medical image analysis
Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearanc...