How Decentralized Artificial Intelligence and Machine Learning Change Medicine, Explained

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It will make the medical experience more interactive and tailored to the user.

There are several key problems that decentralized AI tackles, and provide the user the opportunity to take back control of their healthcare.

The Integral Burden

These solutions can guide the participant in finding and collecting its own medical data. Most people do not have access to their medical information, they do not know where to start and if they do, their knowledge of computer science is limited. They also foster and support an open-source developer community to help innovate tools on their tool platform stacks, to facilitate the integration and collection of data and to present algorithms to interpret the data: a decentralized Kaggle for personalized biology.

Organic and Unbiased Data

The Blockchain is used as triple-entry accounting so we can track and authenticate the data sources. This allows to make great predictions and be able to audit the provenance of the data and perform data forensics and KYD or Know Your Data, processes.

Also for the biased data problem, the technology creates safer healthcare for the user. For example, data coming from randomized control trials are often riddled with bias. The highly selective nature of trials systematically disfavor women, the elderly, and those with additional medical conditions to the ones being studied; pregnant women are mostly entirely ignored.

Privacy Concerns

People may be hesitant to share their medical data over networks where strangers can be lurking. By decentralizing the data over all the users, it is cryptographically timestamped and becomes immutable. Furthermore, Neuron addresses HIPAA requirements by maintaining the information on the edge device, not in the cloud or on a centralized server.

Opportunities Ahead

While the healthcare industry remains far from creating a doctor in a machine, in medicine, there are generalists (GPs) and Specialists. Generalists are analogous to GAI (General AI), unreachable at this point of technological development. But specialists are like vertical AIs and closer to realization. The ABMS (American Board of Medical Specialties) lists more than 150 medical specialties and subspecialties. Neuron has the potential to be the leading player in this sphere.

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