Computational intelligence and neuroscience
Jun 22, 2016
The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of plant disease recognition model, based on leaf image...
The knowledge of the broken rotor bars characteristic frequencies and amplitudes has a great importance for all related diagnostic methods. The monitoring of motor faults requires a high resolution spectrum to separate different frequency components....
Database : the journal of biological databases and curation
Jun 15, 2016
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 7, 2016
The problem of constructing classifiers from multiple annotators who provide inconsistent training labels is important and occurs in many application domains. Many existing methods focus on the understanding and learning of the crowd behaviors. Sever...
In this paper, we propose metric Hashing Forests (mHF) which is a supervised variant of random forests tailored for the task of nearest neighbor retrieval through hashing. This is achieved by training independent hashing trees that parse and encode t...
OBJECTIVE: A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aim...
BACKGROUND: Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for d...
Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of...
Incremental fuzzy clustering combines advantages of fuzzy clustering and incremental clustering, and therefore is important in classifying large biomedical literature. Conventional algorithms, suffering from data sparsity and high-dimensionality, oft...
Statistical methods in medical research
May 30, 2016
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for ...
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