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patient e3
patient.health.eco.br
Where is your data? Shouldn't they be in our personal databases?
But do we have a personal knowledge base?
Unfortunately not yet today!
But now, why don't we have it?
Proposal for effective centralization of all your data in an Intelligent Graph DB in the cloud:
A characteristic that is surprising today is that people do not know at all where their data is. They fly around the world and are only accessed through login. Everything converges before the user interacts with the different applications and websites whose sole objective is purchasing. This process ends, the logout happens and the data disappears, no one knows where your data is. Except for the sad set of steps describing the app screens, but what if the doctor asks if you've ever had a specific symptom? Then the truth comes out! People do not have ownership over their data. They don't even know it exists! And the company's systems are made with specific mass production and consumption goals in mind. They are not modeled and treated in the correct way to be synthesized into knowledge bases. A simple change of focus, from the company to the person, makes all the difference here! Seeking to build knowledge bases of people and user groups with clear and concrete objectives. Enabling users to manage this synthetic knowledge base makes all the difference. And to think that graphs emerged in the early days of computing. Today in Graph Data Science we use some algorithms defined in the 70s, or even from earlier times. With the advancement of knowledge engineering combined with the visualization of complex data proposed by visualization APIs, we will be able to contribute to the construction of super apps. And if we think formally of a complex system, the objective would be compatibility, within the unification proposition proposed by Von Neumann who, before his early death, had the idea of integrating the current architecture that bears his name with the architecture of automatons, also defined by him. Now, leaving formalism aside, in the explanatory sense, the processing would be in the graph itself. It is worth thinking that even at that time the genius saw that the models were compatible.
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By graph.mdpatient.health.eco.br
Where is your data? Shouldn't they be in our personal databases?
But do we have a personal knowledge base?
Unfortunately not yet today!
But now, why don't we have it?
Proposal for effective centralization of all your data in an Intelligent Graph DB in the cloud:
A characteristic that is surprising today is that people do not know at all where their data is. They fly around the world and are only accessed through login. Everything converges before the user interacts with the different applications and websites whose sole objective is purchasing. This process ends, the logout happens and the data disappears, no one knows where your data is. Except for the sad set of steps describing the app screens, but what if the doctor asks if you've ever had a specific symptom? Then the truth comes out! People do not have ownership over their data. They don't even know it exists! And the company's systems are made with specific mass production and consumption goals in mind. They are not modeled and treated in the correct way to be synthesized into knowledge bases. A simple change of focus, from the company to the person, makes all the difference here! Seeking to build knowledge bases of people and user groups with clear and concrete objectives. Enabling users to manage this synthetic knowledge base makes all the difference. And to think that graphs emerged in the early days of computing. Today in Graph Data Science we use some algorithms defined in the 70s, or even from earlier times. With the advancement of knowledge engineering combined with the visualization of complex data proposed by visualization APIs, we will be able to contribute to the construction of super apps. And if we think formally of a complex system, the objective would be compatibility, within the unification proposition proposed by Von Neumann who, before his early death, had the idea of integrating the current architecture that bears his name with the architecture of automatons, also defined by him. Now, leaving formalism aside, in the explanatory sense, the processing would be in the graph itself. It is worth thinking that even at that time the genius saw that the models were compatible.