https://architecture.synthesis.eco.br/ All transactions must respect access, privacy, and intellectual rights. This universe of synthesis is built on demand, generated by the community itself, respecting the interests of each doctor and consequently their patients. The best practices related to the control of rights and information security, already used and specific, defined in the LGPD, GDPR, and HIPAA, must be followed. It is important to reinforce the observation that all intelligence must be applied anonymously. Used only to look for patterns and relationships between events that would be within a single privately stored universe. For example, a medical record could be in a unified database with all of its information, but the only person who would know the patient's name would be the doctor responsible for the diagnostic information. In this case, the meaning of the concept of “synthesis” changes. Occasionally, the aforementioned concept becomes an anonymization process based on the application of algorithms and cryptographic techniques to generate data with the same statistical standard as the original data. Without unlocking keys, the data is an indecipherable code for anyone using it. Note that there are several data synthesis techniques. In some cases, information such as dates must be kept unchanged, as certain analyses may need to know the person's age, for example. The entire process is controlled by the aforementioned protocols: LGPD, GDPR, and HIPAA. Each study is a specific case with its respective needs! But the fact is that a technological leap has occurred in recent years, due to the challenge of overcoming the pandemic.

https://architecture.synthesis.eco.br The super app synthesis.clinic is capable of performing the same functions as a conventional electronic medical record, such as anamnesis, physical examination, consultation of the results of laboratory tests and patient images, even medical management and diagnosis . The system has a single interface for a web platform or mobile application, using the Python programming language to develop the application layer logic. In this scenario, Vercel's cloud platform is proposed together with Next.JS, so that the model is hosted and fed through the data that will come from Aura DB. In the cloud, there are three information input ports: messages from the mobile interface; information through the Back Endi server APIs; and the Next/React client interface. The development of the presentation layer uses the Chakra graphics component library to assist with user interface layout and components. This project aims to integrate the clinic (or hospital) system and the mobile application through web services, so that data traffic between the systems can be carried out. The data layer is integrated through Cypher queries (CQL) applied directly to the graphs through paths. A classic example of a CQL query is the Shortest Path (shortest path between two nodes or concepts). The technological leap of a Graph DB is being able to perform queries that are impossible for conventional Relational banks for more complex cases, such as the itinerary of a transcontinental air trip. In this dimension, even the best relational DBMS such as Oracle and SQL server or Postgres cannot process certain queries. This fact is explained by the computational paradigm. Graph processing is more efficient for complex data. GDS (Graph Data Science) contributes to this point, creating specific properties in the nodes with metrics of their processing. This allows synchronization with the D3.js (Popoto) and NeoVis visualization APIs that will work on the intelligent Timeline generated by GDS. The knowledge synthesis project's interactive predictions and simulations utilize this innovative concept.

https://architecture.synthesis.eco.br We believe that we can extend our super app concept to other areas, in addition to health, creating a unified console between the person and the environment: Next.js (Vercel); Neo4J (Aura DB); Cloud (GCP) for Apache (Spark/Kafka/Arrow); and Digital Ocen apps for AI with Python. In short, what a company would have the technology. It's annoying that people don't know the importance of having a professional technological structure that could be purchased for the price of a pizza a month. Instead of giving up your data on free platforms that win at both ends (client and content producer), they explicitly sell data that is not yours. And everything is fine. It is free! I might buy one more pizza this month. Culture is important, we believe that the current moment is a watershed. An important point regarding the modeling aspect of Graph DB schemas is their modification, based on the parameters targeted by the models built through GDS (Graph Data Science). Custom schemas can be created with nodes containing properties previously stored in relationships. This is because the Knowledge Engineer has specific needs. Customizations allow you to create the ML Pipeline and training or testing models in GDS. The records will be defined, according to analysis seeking to standardize information specified by the HL7 communication protocol for health systems. The file in the protocol model generated for communication will, therefore, have a single item, the patient, or the map with all its respective information related to the Graph DB, forming the structure of its schema adaptable to the structure of a JSON file. This is considered the main idea taken from the HL7 communication protocol, previously mentioned elsewhere. This process allows all relationships and conventional entities oriented to just a single record to be identified, providing the ability to integrate with external knowledge bases through mapping the relationship between internal and external concepts made possible by APIs for connecting to Graph DBs in the health sector, available at synthesis.clinic The electronic medical record mobile application is integrated with the cloud through a backend project, which allows registering the application using an “API key” identifier from the Next.JS project. Communication is carried out by queries defined within the control methods with the function of carrying out the process of searching/sending data for exchanged messages. Subsequently, its persistence is initiated from the integrated synthesis.eco.br web console (server and client) in the Next.JS language and then recorded in the cloud and finally synchronized in the Graph DB Aura, assembling the map of concepts and relationships that will form part of the patient's medical record.

https://arquitetura.sintese.eco.br Todas as transações devem respeitar o acesso, a privacidade e os direitos intelectuais. Esse universo de síntese é construído sob demanda, gerado pela própria comunidade, respeitando os interesses de cada médico e consequentemente de seus pacientes. Devem ser seguidas as melhores práticas relacionadas ao controle de direitos e segurança da informação, já utilizadas e específicas, definidas na LGPD, GDPR e HIPAA. É importante reforçar a observação de que toda inteligência deve ser aplicada anonimamente. Usada apenas para procurar padrões e relacionamentos entre eventos que estariam dentro de um único universo armazenado de forma privada. Por exemplo, um prontuário médico poderia estar em um banco de dados unificado com todas as suas informações, mas a única pessoa que saberia o nome do paciente seria o médico responsável pelas informações diagnósticas. Neste caso, o significado do conceito de “síntese” muda. Ocasionalmente, o conceito referido passa a ser um processo de anonimização baseado na aplicação de algoritmos e técnicas criptográficas para gerar dados com o mesmo padrão estatístico dos dados originais. Sem chaves de desbloqueio, os dados são um código indecifrável para quem os utiliza. Observe que existem várias técnicas de síntese de dados. Em alguns casos, informações como datas devem ser mantidas inalteradas, pois determinadas análises podem precisar saber a idade da pessoa, por exemplo. Todo o processo é controlado pelos protocolos citados: LGPD, GDPR e HIPAA. Cada estudo é um caso específico com suas respectivas necessidades! Mas o fato é que ocorreu um salto tecnológico nos últimos anos, devido ao desafio de superar a pandemia.

https://arquitetura.sintese.eco.br O super app saude.sintese.de é capaz de realizar as mesmas funções de um prontuário eletrônico convencional, como anamnese, exame físico, consulta de resultados de exames laboratoriais e imagens de pacientes, até mesmo manejo e diagnóstico médico. O sistema possui uma interface única para uma plataforma web ou aplicação mobile, utilizando a linguagem de programação Python para desenvolver a lógica da camada de aplicação. Neste cenário, é proposta a plataforma cloud da Vercel em conjunto com o Next.JS, para que o modelo seja hospedado e alimentado através dos dados que virão do Aura DB. Na nuvem existem três portas de entrada de informações: mensagens da interface móvel; informações através das APIs do servidor Back Endi; e a interface do cliente Next/React. O desenvolvimento da camada de apresentação usa a biblioteca de componentes gráficos Chakra para auxiliar no layout e nos componentes da interface do usuário. Este projeto visa integrar o sistema da clínica (ou hospital) e o aplicativo mobile através de web services, para que seja realizado o tráfego de dados entre os sistemas. A camada de dados é integrada por meio de consultas Cypher (CQL) aplicadas diretamente nos gráficos por meio de caminhos. Um exemplo clássico de consulta CQL é o Shortest Path (caminho mais curto entre dois nós ou conceitos). O salto tecnológico de um BD Graph é poder realizar consultas impossíveis aos bancos relacionais convencionais para casos mais complexos, como o itinerário de uma viagem aérea transcontinental. Nesta dimensão, mesmo os melhores SGBDs relacionais como Oracle e SQL server ou Postgres não conseguem processar determinadas consultas. Este fato é explicado pelo paradigma computacional. O processamento gráfico é mais eficiente para dados complexos. O GDS (Graph Data Science) contribui nesse ponto, criando propriedades específicas nos nós com métricas de seu processamento. Isso permite a sincronização com as APIs de visualização D3.js (Popoto) e NeoVis que funcionarão na Timeline inteligente gerada pelo GDS. As previsões e simulações interativas do projeto de síntese de conhecimento utilizam esse conceito inovador.

https://arquitetura.sintese.eco.br Acreditamos que podemos estender para as demais áreas, além da saúde, o nosso conceito de super app criando um console unificado da pessoa com o ambiente: Next.js (Vercel); Neo4J (Aura DB); Cloud (GCP) para Apache (Spark/Kafka/Arrow); and Digital Ocean apps for IA with Python. Em resumo, que uma empresa teria de tecnologia. Incomoda o fato das pessoas não saberem da importância de ter uma estrutura tecnológica profissional que poderiam ser adquiridos com o preço de uma pizza por mês. Ao invés de abrirem mão dos seus dados em plataformas gratuitas que ganham nas duas pontas (cliente e produtor de conteúdo), vendem os dados que não são seus de forma explícita. E está tudo bem. É gratuíto! Posso comprar mais uma pizza este mês. A cultura é importante, acreditamos que o momento atual é um divisor de águas. Um ponto importante, sobre o aspecto da modelagem dos schemas Graph DB, é a sua modificação, baseada nos parâmetros objetivados pelos modelos construídos através da GDS (Graph Data Science). Podem ser criados schemas customizados com nodos que conterão propriedades anteriormente armazenadas em relacionamentos. Isto porque o Engenheiro do Conhecimento tem necessidades específicas. As customizações permitem que se possa criar o ML Pipeline e Modelos de treinamento ou testes na GDS. Os registros serão definidos, conforme análise buscando a padronização de informações definidas pelo protocolo de comunicação HL7 para sistemas de saúde. O arquivo no modelo do protocolo gerado para a comunicação terá, portanto, em um único item, o paciente, ou o mapa com todas as suas respectivas informações relacionadas ao Graph DB, formando a estrutura do seu schema adaptável à estrutura de um arquivo Json. Considera-se, essa, a principal ideia retirada do protocolo de comunicação HL7, citado anteriormente em outros momentos. O referido processo permite que sejam identificados todos os relacionamentos e entidades convencionais orientadas a apenas um único registro, fornecendo a capacidade de integração com bases de conhecimentos externas através do mapeamento do relacionamento entre os conceitos internos e externos possibilitada por APIs para conexão com os Graph DBs da área da saúde, disponibilizadas pelo sintese.eco.br. A aplicação móvel do prontuário eletrônico é integrada à nuvem através de um projeto backend, que permite registrar o aplicativo com o uso de um identificador “API key” do projeto Next.JS. A comunicação é realizada pelas consultas definidas dentro dos métodos de controle com a função de realizar o processo de busca/envio de dados das mensagens trocadas. Posteriormente é iniciada a sua persistência a partir do console web health.eco.br integrado (servidor e cliente) na linguagem Next.JS e, então, gravados na nuvem e, finalmente sincronizados no Graph DB Aura, montando o mapa de conceitos e relacionamentos que comporão o próprio prontuário do paciente.

https://technology.synthesis.eco.br/ In order not to be extensive on this subject, we mention the concept of “liquid relations” defined by Zygmunt Bauman when talking about postmodern society. Fortunately, the author brings a positive idea on the topic of humanity. We believe that everyone's contribution in this aspect is fundamental to solving this existential dilemma. Changing the role of technology from a great villain to a positive instrument of transformation is what motivates the Knowledge Synthesis project. We want to transform users into knowledge engineers! We will work very hard to make the best possible technology available to people, which today is only accessible to large companies. Here comes the key point: one person will have a system larger than that of a large company. Each individual will build their system throughout their life. In all basic and non-subjective aspects, the systems will be approximately equal, so it is no longer the system that will be developed. The entire basic and standardized system is already developed and ready for use. But not the base! So in this universe, the complete reversal of the process occurs. The person who must prepare and model your base to make your data available to a given application. This idea seems strange to the current computational world of continuous development of systems that have no end, but if we stop for a moment and think, for everything in life people have to prepare to participate and achieve. University entrance exams, public exams, changing habits in the transition from single to married life, constant and continuous learning to raise children, and, or even, presenting evidence in court when subpoenaed by the judge. All the processes of life in society are already defined, they are only improving. We must think of a system that allows complex interaction! We are today in the era of super protocols, such as ChanLink, Ocean protocol, SDAO, and Agix, and we are heading into the era of super applications in a few years. Our objective is that these super apps are those of people and not those of companies. Furthermore, direct all our energies to building a better world. Therefore, we will always be developing technology from people to people.

https://technology.synthesis.eco.br In our synthetic universe, data from companies' products reaches the secure Graph BD, the person interacts in this BD Graph ZK (Zero Knowledge), chooses the best products (sneakers) for their profile (of use) based on their logs, in the records of friends and sports experts. Once the choice is made, the user will request an anonymous purchase, collect the data they want to keep from their analysis and discard them, or save the data in a database in their profile. The important thing is that the company does not keep any data from our members, everything is protocoled and defined so that interactions and syntheses occur in ZK Graphs owned by people, strange to think that the person has to enter the company's store website (amazon, best buy, nike, etc) if now she can receive everything she needs and make a ZK choice with anonymous purchase. Once the transaction is made, people receive no publicity about anything, as there is no information about the person outside of their Graph Universe. Except in specific and controlled conditions, to be used only for your benefit, as support for medical diagnosis. The HIPAA (Health Insurance Portability and Accountability Act) protocol, long applied in the healthcare sector, is cited here as a reference for use. The development of computational models to support Synthesis solutions is based on the perspective of integral knowledge mapping in a Graph DB. With dynamic interaction, it is possible to create schemas in these Graph DBs supported by the Object Process Methodology defined by Dov Dori from the Israel Institute of Technology, seeking a more meaningful experience for the user who becomes part of the knowledge base construction process in a simple way and intuitive. Multiple viewing perspectives are allowed, providing a real analysis of the data based on its relationships. A fact that would be impossible for great specialists if they were processed by a relational database. This difference motivates the direction of the knowledge synthesis project.