The rigor of the academic and professional world has required the development of a level of excellence in (dynamic) reading and writing skills for journals and conferences. To date, more than five hundred non-technical books have been read at a speed of over 350 words per second. To improve memorization, the Spaced Repetition System (Anki software) is used.

Acting as a graph md data science specialist and leading high-performance teams in projects to develop intelligent complex digital ecosystems. Daily work involves acquiring and modeling complex data; using GDS algorithms through intelligent agents; and developing the super app graph.md for the digital ecosystem for synthesizing medical knowledge. An important point is the constant contact with complex problems, for which the best logic is always sought to meet the needs of the GDS algorithms.

Identifying and automating the flow of knowledge is a basic requirement of a Graph Data Science project. The entire focus of the work on software development and the creation of architecture for intelligent complex ecosystems is for this purpose. Linked to the early days of AI applied to healthcare, a fact that allowed the acquisition of knowledge of Machine Learning, Vertex AI, and Aura GDS, as well as their respective algorithms and statistical models. Likewise, the study of the main models of pattern recognition, knowledge engineering, complex systems, and abstract models. For example, the law of least effort was defined by Kingsley Zipf, from Harvard, in 1950, which establishes the same linguistic relationship between a 3-year-old child and William Shakespeare and also defines how American cities were created and developed. The concepts: OPM (Object Process Methodology), which removes the method from the class, by creating a methodology with two main elements (Object and Process at the same hierarchical level). Used for modeling and development of aerospace systems defined by Dov Dori from the Israel Institute in partnership with Edward Crowley from MIT. Last but not least, the concept of different levels of abstraction of the computational model of a complex intelligent digital ecosystem (I'm a Strange Loop), defined by Douglas Hofstadter, from Indiana University.

Concluding these brief ideas on how to graph md could add value to projects related to the health area, acting as a connecting link between AI, through Graph Data Science, and medicine. We are proud to say that we have developed an innovative GDS model for the graph.md platform, unique in the world, with our investment of 1 million, in the last 2 years alone, now with the support of the neo4j startup program, which stores all of the patients' diseases and symptoms in a graph md. But to carry out daily activities, at this pace of development required by high technology, it is necessary to manage time in the best possible way. In this sense, to maintain high professional and personal performance, one must be as organized as possible to meet all challenges. Thank you for your interest in learning a little about the history of graph.md, and now, for the time dedicated to reading this professional profile.

Current knowledge synthesis project developed by graph md with Data Science technology supported by the neo4j startup program. The development architecture of this Dynamic Web system for knowledge synthesis based on GDS using Graph DB on the Neo4j Aura DS platform. The modeling of this complex system is based on the Graph DB and OPM (Object Process Methodology) schemes. Technologies focused on the development of air/space traffic control systems defined by researchers from the Israel Institute of Technology in conjunction with MIT.

Description: The development of computational models to support new technological solutions is based on the perspective of integral mapping of knowledge in a Graph DB. With dynamic interaction, it is possible to create Graph DB schemes supported by the Object Process Methodology, seeking a more meaningful experience for the user who becomes part of the knowledge base construction process simply and intuitively. Multiple visualization perspectives are allowed, providing a real analysis of the data based on their relationships. A fact that would be impossible for great experts if they were processed by a relational database. This difference motivates the direction of the project. The idea is to integrate the solution into the super web app graph.md and customize it for the neo4J desktop, allowing for even more fluid usability than the browser. In future versions, we intend to use both forms together, including the use of the D3js API, bringing the most sophisticated algorithms from Python Anaconda after processing Big Data by Spark, thus allowing a greater degree of interactivity using Java Spring Data Neo4j.

Please note that due to contractual confidentiality issues, some participation in the projects cannot be disclosed in this document.

Open StartUp Science Innovation: Project to develop an Open Science model for the startup ecosystem of graph.md.

A unique concept with countless ways to innovate through the Intelligent Idea Management Program, Open Innovation, Squads, and Innovation Hubs, among others.

Computer model to support the diagnosis of Epilepsy

Description: The development of computer models based on the perspective of the specialist physician aims to transform clinical information into knowledge to propose the creation of more efficient systems to support neurological diagnosis.

Status: Completed;

Nature: Research projects

Students involved: Doctorate;

Members: Daniel da Silva Cotrim (Responsible); André Luis Fernandes Palmini.

Development and validation of a low-cost teleradiology system 

Description: Develop and validate a low-cost solution to enable the digitalization, storage, and electronic transmission of conventional radiological exams.

Status: Completed;

Nature: Research projects

Students involved: Undergraduate (2); Master's degree (1);

Members: Daniel da Silva Cotrim; Ana Maria Marques da Silva (Responsible)

Financier(s): Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul-FAPERGS.

Technological development projects

Electronic Medical Record Hospital do Coração de São Paulo

Description: Analysis of patient data from Hospital do Coração de São Paulo for the development and implementation of the HCor electronic medical record.

Status: Completed;

Nature: Technological development projects

Members: Daniel da Silva Cotrim (Responsible).

Experimental environment based on grid technology for training human resources in Nuclear Medicine

Description: The objective of the project is to develop a portal that provides a set of user-friendly, scalable, and easily accessible tools for simulations of images in nuclear medicine, within a controlled collaborative grid experiment for training human resources in nuclear medicine.

Status: Completed;

Nature: Technological development projects

Students involved: Undergraduate (1); Academic Master's degree (1);

Members: Daniel da Silva Cotrim; Ana Maria Marques da Silva (Responsible)

Financier(s): Regional Fund for Digital Innovation in Latin America and the Caribbean-FRIDA.

Pattern Recognition Applied to Medical Diagnosis in Embedded System (FINEP/PUCRS/USP)

Description: The objective is to develop an embedded system for pattern recognition in medical images to support diagnosis.

Status: Completed;

Nature: Technological development projects

Students involved: Undergraduate; Master's degree; Doctorate;

Members: Daniel da Silva Cotrim; Ana Maria Marques da Silva; Eduardo Augusto Bezerra; Fernanda Rocha da Trindade; Pedro Xerxenesky; Fabiano Hessel (Responsible)

Financier(s): Financier of Studies and Projects-FINEP.

Development of a Java plugin for Tomographic Reconstruction and Visualization in Nuclear Medicine

Description: Develop a system for tomographic reconstruction, visualization, and quantification of medical images that allows the quantitative interpretation of exams acquired in a clinical environment, in JAVA language.

Status: Completed

Nature: Technological development projects

Members: Daniel da Silva Cotrim; Ana Maria Marques da Silva (Responsible); Aline Machado Furlan; Michele Alberton de Andrade; Marcus Vinícius da Silva Costa.

INPACSS - A Component for Instantaneous Storage and Retrieval of Medical Images

Description: INPACSS was the first DICOM Server used at PUCRS's São Lucas Hospital, allowing the management of medical images generated at the hospital, which involved their storage, transmission, retrieval, and integration with distributed viewing stations, online databases, and integration with different types of medical equipment (US, X-ray, computed tomography and magnetic resonance). Therefore, the objective of this project is to develop a component, based on an already approved communication protocol, for the storage and retrieval of medical images. A technological innovation in this component is the implementation of streaming technology, which allows the transfer of images between the different equipment in a hospital instantly. Immediate viewing of the image is possible because its definition gradually increases during the transmission process. Another important innovation is the integration with visualization systems available on the market to take advantage of their medical image analysis functionalities.

Status: Completed;

Nature: Technological development projects

Responsible: Daniel da Silva Cotrim (DSC Me; Partner Company)

Financier(s): Rio Grande do Sul State Research Support Foundation-FAPERGS