AIMC Topic: Algorithms

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An unsupervised learning approach for tracking mice in an enclosed area.

BMC bioinformatics
BACKGROUND: In neuroscience research, mouse models are valuable tools to understand the genetic mechanisms that advance evidence-based discovery. In this context, large-scale studies emphasize the need for automated high-throughput systems providing ...

A new near-lossless EEG compression method using ANN-based reconstruction technique.

Computers in biology and medicine
Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as discrete cosine transform (DCT) and wavelet and usually c...

Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning.

PloS one
De novo membrane protein structure prediction is limited to small proteins due to the conformational search space quickly expanding with length. Long-range contacts (24+ amino acid separation)-residue positions distant in sequence, but in close proxi...

An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

Computer methods and programs in biomedicine
OBJECTIVE: This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images.

Deep Learning in Medical Imaging: General Overview.

Korean journal of radiology
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient...

Drug Target Prediction by Multi-View Low Rank Embedding.

IEEE/ACM transactions on computational biology and bioinformatics
Drug repositioning has been a key problem in drug development, and heterogeneous data sources are used to predict drug-target interactions by different approaches. However, most of studies focus on a single representation of drugs or proteins. It has...

An inference method from multi-layered structure of biomedical data.

BMC medical informatics and decision making
BACKGROUND: Biological system is a multi-layered structure of omics with genome, epigenome, transcriptome, metabolome, proteome, etc., and can be further stretched to clinical/medical layers such as diseasome, drugs, and symptoms. One advantage of om...

Modeling long-term human activeness using recurrent neural networks for biometric data.

BMC medical informatics and decision making
BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three ty...

Cascade recurring deep networks for audible range prediction.

BMC medical informatics and decision making
BACKGROUND: Hearing Aids amplify sounds at certain frequencies to help patients, who have hearing loss, to improve the quality of life. Variables affecting hearing improvement include the characteristics of the patients' hearing loss, the characteris...

NFPscanner: a webtool for knowledge-based deciphering of biomedical networks.

BMC bioinformatics
BACKGROUND: Many biological pathways have been created to represent different types of knowledge, such as genetic interactions, metabolic reactions, and gene-regulating and physical-binding relationships. Biologists are using a wide range of omics da...