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Models, Immunological

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Computational Intelligence for Medical Imaging Simulations.

Journal of medical systems
This paper describes how to simulate medical imaging by computational intelligence to explore areas that cannot be easily achieved by traditional ways, including genes and proteins simulations related to cancer development and immunity. This paper ha...

Towards the development of robot immune system: A combined approach involving innate immune cells and T-lymphocytes.

Bio Systems
Mobile robots in uncertain and unstructuredenvironments frequently encounter faults. Therefore, an effective fault detection and recovery mechanism is required. One can possibly investigate natural systems to seek inspiration to develop systems that ...

Analysis of defective pathways and drug repositioning in Multiple Sclerosis via machine learning approaches.

Computers in biology and medicine
BACKGROUND: Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.

Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

Journal of drugs in dermatology : JDD
BACKGROUND: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired during a treatment or else present itself from the beginning. To date, no biomarkers are known that may reliably guide clinicians in predicting respons...

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

Frontiers in immunology
RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testin...

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

Cancer immunology research
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...

Unveiling the immune infiltrate modulation in cancer and response to immunotherapy by MIXTURE-an enhanced deconvolution method.

Briefings in bioinformatics
The accurate quantification of tumor-infiltrating immune cells turns crucial to uncover their role in tumor immune escape, to determine patient prognosis and to predict response to immune checkpoint blockade. Current state-of-the-art methods that qua...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

Computer methods in biomechanics and biomedical engineering
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required fo...