AIMC Topic: Algorithms

Clear Filters Showing 21891 to 21900 of 28713 articles

A Fast SVM-Based Tongue's Colour Classification Aided by -Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis.

Journal of healthcare engineering
In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable ...

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis.

PloS one
A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipola...

Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Biomolecular controlled annotations have become pivotal in computational biology, because they allow scientists to analyze large amounts of biological data to better understand test results, and to infer new knowledge. Yet, biomolecular annotation da...

Feature selection using ant colony optimization with tandem-run recruitment to diagnose bronchitis from CT scan images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Computer-aided diagnosis (CAD) plays a vital role in the routine clinical activity for the detection of lung disorders using computed tomography (CT) images. It serves as a source of second opinion that radiologists may con...

Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection.

Computers in biology and medicine
Different types of breast cancer are affecting lives of women across the world. Common types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular carcinoma, Medullary carcinoma, and Invasive lobular carcinoma (ILC). While...

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

IEEE transactions on neural networks and learning systems
The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in ...

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. ...

Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images.

Computational biology and chemistry
Protein structure prediction and analysis are more significant for living organs to perfect asses the living organ functionalities. Several protein structure prediction methods use neural network (NN). However, the Hidden Markov model is more interpr...

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

BMC medical informatics and decision making
BACKGROUND: Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (...