AIMC Topic: Algorithms

Clear Filters Showing 22311 to 22320 of 28713 articles

Deep Neural Networks for Identifying Cough Sounds.

IEEE transactions on biomedical circuits and systems
In this paper, we consider two different approaches of using deep neural networks for cough detection. The cough detection task is cast as a visual recognition problem and as a sequence-to-sequence labeling problem. A convolutional neural network and...

Automated Detection of P. falciparum Using Machine Learning Algorithms with Quantitative Phase Images of Unstained Cells.

PloS one
Malaria detection through microscopic examination of stained blood smears is a diagnostic challenge that heavily relies on the expertise of trained microscopists. This paper presents an automated analysis method for detection and staging of red blood...

Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Through sequence-based classification, this paper tries to accurately predict the DNA binding sites of transcription factors (TFs) in an unannotated cellular context. Related methods in the literature fail to perform such predictions accurately, sinc...

A Novel EMG Interface for Individuals With Tetraplegia to Pilot Robot Hand Grasping.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper introduces a new human-machine interface for individuals with tetraplegia. We investigated the feasibility of piloting an assistive device by processing supra-lesional muscle responses online. The ability to voluntarily contract a set of s...

Machine learning approaches to personalize early prediction of asthma exacerbations.

Annals of the New York Academy of Sciences
Patient telemonitoring results in an aggregation of significant amounts of information about patient disease trajectory. However, the potential use of this information for early prediction of exacerbations in adult asthma patients has not been system...

Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson's Patients.

Sensors (Basel, Switzerland)
We still do not know how the brain and its computations are affected by nerve cell deaths and their compensatory learning processes, as these develop in neurodegenerative diseases (ND). Compensatory learning processes are ND symptoms usually observed...

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

PloS one
Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that ...

ACID: Association Correction for Imbalanced Data in GWAS.

IEEE/ACM transactions on computational biology and bioinformatics
Genome-wide association study (GWAS) has been widely witnessed as a powerful tool for revealing suspicious loci from various diseases. However, real world GWAS tasks always suffer from the data imbalance problem of sufficient control samples and limi...

A Self-Organizing Incremental Neural Network based on local distribution learning.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines the advantages of incr...

Estimating complicated baselines in analytical signals using the iterative training of Bayesian regularized artificial neural networks.

Analytica chimica acta
The present work deals with the development of a new baseline correction method based on the comparative learning capabilities of artificial neural networks. The developed method uses the Bayes probability theorem for prevention of the occurrence of ...