AIMC Topic: Algorithms

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A Cancer Gene Selection Algorithm Based on the K-S Test and CFS.

BioMed research international
BACKGROUND: To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S) test and correlation-based feature selec...

Geminivirus data warehouse: a database enriched with machine learning approaches.

BMC bioinformatics
BACKGROUND: The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic los...

Online cross-validation-based ensemble learning.

Statistics in medicine
Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinit...

A Grouping Particle Swarm Optimizer with Personal-Best-Position Guidance for Large Scale Optimization.

IEEE/ACM transactions on computational biology and bioinformatics
Particle Swarm Optimization (PSO) is a popular algorithm which is widely investigated and well implemented in many areas. However, the canonical PSO does not perform well in population diversity maintenance so that usually leads to a premature conver...

Modeling and evaluation of hand-eye coordination of surgical robotic system on task performance.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robotic-assisted minimally invasive surgery changes the direct hand and eye coordination in traditional surgery to indirect instrument and camera coordination, which affects the ergonomics, operation performance, and safety.

Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urge...

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

BMC medical imaging
BACKGROUND: Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit ...

Improving Classification Performance through an Advanced Ensemble Based Heterogeneous Extreme Learning Machines.

Computational intelligence and neuroscience
Extreme Learning Machine (ELM) is a fast-learning algorithm for a single-hidden layer feedforward neural network (SLFN). It often has good generalization performance. However, there are chances that it might overfit the training data due to having mo...

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

Journal of theoretical biology
The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral metho...

Dysphonic Voice Pattern Analysis of Patients in Parkinson's Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods.

Computational and mathematical methods in medicine
Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and related phonation disorders. In this paper, we first study the linear correlations between 22 voice parameters of fundamental frequency variability, ampl...