AI Medical Compendium Journal:
Journal of theoretical biology

Showing 1 to 10 of 59 articles

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.

Journal of theoretical biology
Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the toll of HIV and AIDS. With an estimated 10.6 million new TB cases worldwide in 2022, the gravity of...

Statistical inference and neural network training based on stochastic difference model for air pollution and associated disease transmission.

Journal of theoretical biology
A polluted air environment can potentially provoke infections of diverse respiratory diseases. The development of mathematical models can study the mechanism of air pollution and its effect on the spread of diseases. The key is to characterize the in...

Optimal STI controls for HIV patients based on an efficient deep Q learning method.

Journal of theoretical biology
We investigate an efficient computational tool to suggest useful treatment regimens for people infected with the human immunodeficiency virus (HIV). Structured treatment interruption (STI) is a regimen in which therapeutic drugs are periodically admi...

A muti-modal feature fusion method based on deep learning for predicting immunotherapy response.

Journal of theoretical biology
Immune checkpoint therapy (ICT) has greatly improved the survival of cancer patients in the past few years, but only a small number of patients respond to ICT. To predict ICT response, we developed a multi-modal feature fusion model based on deep lea...

Deep learning characterization of brain tumours with diffusion weighted imaging.

Journal of theoretical biology
Glioblastoma multiforme (GBM) is one of the most deadly forms of cancer. Methods of characterizing these tumours are valuable for improving predictions of their progression and response to treatment. A mathematical model called the proliferation-inva...

An RNA-based theory of natural universal computation.

Journal of theoretical biology
Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal compu...

Dynamical robustness and its structural dependence in biological networks.

Journal of theoretical biology
We discuss the dynamical robustness of biological networks represented by directed graphs, such as neural networks and gene regulatory networks. The theoretical results indicate that networks with low indegree variance and high outdegree variance are...

A minimal model of the interaction of social and individual learning.

Journal of theoretical biology
Learning is thought to be achieved by the selective, activity dependent, adjustment of synaptic connections. Individual learning can also be very hard and/or slow. Social, supervised, learning from others might amplify individual, possibly mainly uns...

Entropy, mutual information, and systematic measures of structured spiking neural networks.

Journal of theoretical biology
The aim of this paper is to investigate various information-theoretic measures, including entropy, mutual information, and some systematic measures that are based on mutual information, for a class of structured spiking neuronal networks. In order to...

Predicting protein-peptide binding sites with a deep convolutional neural network.

Journal of theoretical biology
MOTIVATION: Interactions between proteins and peptides influence biological functions. Predicting such bio-molecular interactions can lead to faster disease prevention and help in drug discovery. Experimental methods for determining protein-peptide b...