AIMC Topic:
Supervised Machine Learning
Clear Filters Showing 1381 to 1390 of 1635 articles
Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.
Journal of theoretical biology
Apr 2, 2015
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimen...
A semi-supervised learning framework for biomedical event extraction based on hidden topics.
Artificial intelligence in medicine
Apr 1, 2015
OBJECTIVES: Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, du...
Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Mar 22, 2015
BACKGROUND/PURPOSE: Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature ...
L1-norm locally linear representation regularization multi-source adaptation learning.
Neural networks : the official journal of the International Neural Network Society
Feb 25, 2015
In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the larg...
A semi-supervised learning approach for RNA secondary structure prediction.
Computational biology and chemistry
Feb 20, 2015
RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because o...
Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.
IEEE transactions on bio-medical engineering
Feb 10, 2015
Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need...
Pervasive Sound Sensing: A Weakly Supervised Training Approach.
IEEE transactions on cybernetics
Feb 6, 2015
Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smart...
Adaptive semi-supervised recursive tree partitioning: The ART towards large scale patient indexing in personalized healthcare.
Journal of biomedical informatics
Feb 3, 2015
With the rapid development of information technologies, tremendous amount of data became readily available in various application domains. This big data era presents challenges to many conventional data analytics research directions including data ca...
Active-learning strategies in computer-assisted drug discovery.
Drug discovery today
Dec 9, 2014
High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the s...
Computer-aided diagnosis from weak supervision: a benchmarking study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 20, 2014
Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) applications. The bottleneck of this technique is its demand for fine grained expert annotations, which are tedious for medical image analysis applicatio...
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