AI for Finding Cures from Traditional Remedies

Throughout the world, there are rare diseases. In remote regions of the world, there is the risk of rare diseases in small communities. Relative to the earth's population, a rare disease found in a small, remote communities are a population size that is likely an extremely small percentage of the earth's population.

  With traditional remedies for rare diseases, AI can be used to possibly discover the molecules that are the keys for treatment. 

This can be accomplished by using artificial intelligence in the form convolutional neural networks (CNN) to discover specific molecules in traditional herbal remedies for the treatment of rare diseases. The program encourages the protection of known rare plants as well as encourages the archiving of relatively unknown rare plants. One approach may be by the CNN-type application DOVE.

 For example, coconut oil has been found to prevent seizures. The key ingredient in the oil is decanoic or capric acid which appears to be, by means of its geometry and electromagnetic charges, able to act as an insulator as it bonds with the AMPA receptor because of it geometry. With CNN, the "lock and key" geometry of capric acid and the AMPA receptor inhibition can be matched with chemicals found in nature that might be even more effective. The system works much like the classical process of machine vision identifying a specific collection of images that are in the same classification, where this system matches the "lock and key". 

  For this application, convolutional neural networks can match what molecule could substitute for capric acid in terms of the geometry and electromagnetic forces, in terms of interacting with the AMPA receptor. Capric acid may control seizures for a general population. However, a rare disease may require a different type of molecule for treating the AMPA receptor.

  In terms of minimizing steps involved and conserving energy, CNNs find the features in the data processed. In many machine learning applications, the features of a molecule, with CNNs, can be matched to the features of a molecule that may be found in a variety of herbal remedies throughout the world. In other words, the geometry of a molecule that treats a rare disease may be found by the CNNs matching the geometry to that which is needed as a cure.

Energy Conservation

1. Energy can be conserved by minimizing the number of molecules that are part of the search function for molecular docking. This minimization function can be assisted by starting from plant-based molecules of remedies considered to be medicinal. 
2. In terms of alternative energy resources for power this technology and access to type of plants that may be remedies, regions like Central America get their electricity from mostly alternative energy sources. 

PROPOSED SOLUTION FOR ENERGY CONSERVATION:

A free online course for providing the necessary CNN computer programming and database resources in those countries where alternative energy is a significant source for total electrical output.

With epilepsy, there are plants-based molecules like the flavonoids of which research has shown to have the potential to be anti-convulsant.

  The implication is that cures for rare disease may be able to be discovered and that preventative strategies may be able to be implemented as well. For example, a rare disease for epilepsy may be able to be managed by the use of resources of existing plants.

The solution may benefit those who struggle with rare disease, especially in remote communities.

The idea appears to be innovative.

The solution may help others.

No

It encourages the use of traditional remedies for finding cures. This can help the environment as well as save of power requirements for AI and machine learning mechanisms.

The goal for next year as well as well as the next five years is to make progress in finding a cure for a rare disease.

The ideal measurement of progress towards the impact goals would be the discovery of a cure for a rare disease, essentially a binary measurement of ideal progress with zero being no discoveries and one being the existence of a discovery from this proposed system.

'In simple terms, the expectation for the solution to have an impact on the problem is for the solution to be a part of making a discovery for a cure for a rare disease.

The core technology that powers the solution is the convolutional neural network (CNN) for identify possible matches to the molecular structure of the virus or other structure that is causal for a rare disease.

1

I have been working on this type of solution for several years.

The solution incorporates diversity, equity, and inclusivity because it encourages diverse communities to know about local herbal remedies that may have traditionally been beneficial for the treatment of rare diseases. These herbal remedies can benefit the same communities with the use of artificial intelligence for the analysis of how or if the remedies have a key component for the treatment of rare diseases.

    The business model is for the solution to be presented as a free online training program. Because it is an artificial intelligence application, there is the consumption of electrical power for the computations. However, the energy conservation component can be achieved in part by the training program service being afforded in countries that produce close to 90% of their electric output from alternative energy sources.  

  Because it is an online course, the expenses are minimal and are presently being paid for as a self-funded enterprise. The goal would be for grants from foundations to support the free service.

The plan for financial sustainability would be for grants to support the project in much the way public television is sustained. Fortunately, the costs are minimal because it is an online course.