Advanced specialization in software and system architecture and development, machine learning engineering, and enterprise IT strategy. Developed high-level skills in designing intelligent systems, training predictive data models, and deploying robust digital infrastructures to solve complex business problems. Designed and implemented an advanced interoperability system for integrating ABI systems in healthcare environments with real world application.
Bachelor's degree in Engineering and Management of Information Systems
Focused on building a strong foundation in software engineering, database management, and business processes. Developed core competencies in application development, data modeling, and analyzing organizational workflows to align technology with business goals.
Thesis
Thesis2024
ABI Systems Integration in Healthcare
João Guedes
University of Minho
The integration of adaptive business intelligence (ABI) systems into the healthcare industry has the potential to revolutionize the way organizations approach data analysis and decision making. By providing real-time, actionable insights and enabling organizations to continuously adapt and evolve, ABI has the potential to drive better outcomes, reduce costs, and improve the overall quality of patient care. This dissertation work explores the integration of ABI systems in the healthcare industry, investigating the benefits, challenges, and opportunities of implementation. The study was conducted through a combination of literature review and case studies of healthcare organizations that have successfully integrated ABI systems into their operations. After the case studies were gathered and literature review completed a plan and development of an ABI implementation solution architecture was undertaken that could interact with external environments through interoperability resources, as well as a practical prototype to test said architecture. During the development of the solution, the research focus also extended to best practices and methodologies in modern, efficient and secure software development.
Interoperability Architecture proposal for Adaptive Business Intelligence Systems in Healthcare Environments
João Guedes
Procedia Computer Science
The integration of systems for adaptive business intelligence (ABI) in the healthcare industry has the potential to revolutionize and reform the way organizations approach data analysis and decision-making. By providing real-time, actionable insights and enabling organizations to continuously adapt and evolve, ABI has the potential to drive better outcomes, reduce costs and improve the overall quality of patient care. This article proposes an interoperability architecture that allows the seamless use and integration of HL7 messages and the information they contain as an interface with these systems. The proposed architecture follows a microservices paradigm with an emphasis on its modularity and distribution capacity and is part of an effort to achieve interoperability and ease of integration with ABI systems, while never neglecting key characteristics such as speed, security and the best practices in software development and architecture.
Revisioning Healthcare Interoperability System for ABI Architectures: Introspection and Improvements
João Guedes
MDPI
The integration of systems for Adaptive Business Intelligence (ABI) in the healthcare industry has the potential to revolutionize and reform the way organizations approach data analysis and decision-making. By providing real-time actionable insights and enabling organizations to continuously adapt and evolve, ABI has the potential to drive better outcomes, reduce costs, and improve the overall quality of patient care. The ABI Interoperability System was designed to facilitate the usage and integration of ABI systems in healthcare environments through interoperability resources like Health Level 7 (HL7) or Fast Healthcare Interoperability Resources (FHIR). The present article briefly describes both versions of this software, learning about their differences and improvements, and how they affect the solution. The changes introduced in the new version of the system will tackle code quality with automated tests, development workflow, and developer experience, with the introduction of Continuous Integration and Delivery pipelines in the development workflow, new support for the FHIR pattern, and address a few security concerns about the architecture. The second revision of the system features a more refined, modern, and secure architecture and has proven to be more performant and efficient than its predecessor. As it stands, the Interoperability System poses a significant step forward toward interoperability and ease of integration in the healthcare ecosystem.