AI Medical Compendium Journal:
IET systems biology

Showing 21 to 30 of 32 articles

Chatteringfree hybrid adaptive neuro-fuzzy inference system-particle swarm optimisation data fusion-based BG-level control.

IET systems biology
In this study, a closed-loop control scheme is proposed for the glucose-insulin regulatory system in type-1 diabetic mellitus (T1DM) patients. Some innovative hybrid glucose-insulin regulators have combined artificial intelligence such as fuzzy logic...

Adaptive back-stepping cancer control using Legendre polynomials.

IET systems biology
Here, a model-free controller for cancer treatment is presented. The treatment objective is to find a proper drug dosage that can reduce the population of tumour cells. Recently, some solutions have been proposed according to the control theory. In t...

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach.

IET systems biology
The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B-cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to dev...

Fuzzy cognitive map based approach for determining the risk of ischemic stroke.

IET systems biology
Stroke is the third major cause of mortality in the world. The diagnosis of stroke is a very complex issue considering controllable and uncontrollable factors. These factors include age, sex, blood pressure, diabetes, obesity, heart disease, smoking,...

Prediction of drug synergy score using ensemble based differential evolution.

IET systems biology
Prediction of drug synergy score is an ill-posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression-based machine learning technique has an ability to minimise the drug synergy pred...

Cancers classification based on deep neural networks and emotional learning approach.

IET systems biology
In the present era, enormous factors contribute to causing cancer. So cancer classification cannot rely only on doctor's thoughts. As a result, intelligent algorithms concerning doctor's help are inevitable. Therefore, the authors are motivated to su...

Design of dynamic genetic memory.

IET systems biology
In electronic systems, dynamic random access memory (DRAM) is one of the core modules in the modern silicon computer. As for a bio-computer, one would need a mechanism for storage of bio-information named 'data', which, in binary logic, has two level...

Bogdanov-Takens bifurcation in a neutral BAM neural networks model with delays.

IET systems biology
In this study, the authors first discuss the existence of Bogdanov-Takens and triple zero singularity of a five neurons neutral bidirectional associative memory neural networks model with two delays. Then, by utilising the centre manifold reduction a...

Sparse electrocardiogram signals recovery based on solving a row echelon-like form of system.

IET systems biology
The study of biology and medicine in a noise environment is an evolving direction in biological data analysis. Among these studies, analysis of electrocardiogram (ECG) signals in a noise environment is a challenging direction in personalized medicine...

In silico discovery of significant pathways in colorectal cancer metastasis using a two-stage optimisation approach.

IET systems biology
Accurate and reliable modelling of protein-protein interaction networks for complex diseases such as colorectal cancer can help better understand mechanism of diseases and potentially discover new drugs. Different machine learning methods such as emp...