Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene...
Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of...
PURPOSE: Cancer care involves extensive knowledge about numerous chemotherapy drugs and chemotherapy regimens. This information is constantly evolving, and there has been no freely available, comprehensive, centralized repository of chemotherapy info...
Glaucocalyxin A (GLA) is a phytochemical component with multiple pharmacological activities; however, glaucocalyxin A's wider use has been restricted by its poor solubility. In this study, GLA nanosuspensions were prepared with precipitation-combined...
Since Ambros' discovery of small non-protein coding RNAs in the early 1990s, the past two decades have seen an upsurge in the number of reports of predicted microRNAs (miR), which have been implicated in various functions. The correlation of miRs wit...
Clinical pharmacology in drug development
Jan 26, 2015
PURPOSE: Rucaparib is a potent Poly (ADP-ribose) Polymerase (PARP) inhibitor currently under clinical development. The objectives of this analysis were to establish population PK and PK/PD models for rucaparib, and to evaluate the predictability of P...
For cancer classification problems based on gene expression, the data usually has only a few dozen sizes but has thousands to tens of thousands of genes which could contain a large number of irrelevant genes. A robust feature selection algorithm is r...
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...
IEEE journal of biomedical and health informatics
Jul 30, 2014
Machine learning is being used in a wide range of application domains to discover patterns in large datasets. Increasingly, the results of machine learning drive critical decisions in applications related to healthcare and biomedicine. Such health-re...
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