An AI-Integrated FHIR Data Model To Assist in Cancer Treatment
Product Overview
Client’s goals
The clinic needed an AI-based app solution that could enhance diagnostic accuracy and help make cancer treatment plans more personalized.
Implementation
To implement our solution, we divided the process into several key stages.
Discovery
First, we started by conducting a current state analysis, then we moved on to defining the future state of a system and performing a gap analysis.
Business Analysis
The next step was to spot the key advantages that a new AI solution could bring. We also defined the project’s scope and main objectives and gathered detailed information about current workflows.
Crafting Initial Design and Choosing Tech Stack
Our experts created the solution's architecture and selected relevant technology that supported FHIR standards and AI capabilities.
Estimation and Road Mapping
Our experts worked on data mapping in healthcare to create a detailed project plan aligned with the client’s expectations.
UX/UI Design
Our designers focused on creating a user-friendly and intuitive user experience and interface.
Software Development
Our software engineers developed robust and scalable backend and frontend components for the solution.
QA & Testing
The QA engineers conducted careful testing, including unit, integration, and user acceptance tests, to ensure the solution met all requirements and was free of critical bugs.
Project Delivery
Finally, we delivered the project, providing the client with a comprehensive FHIR-based AI solution, along with all necessary documentation and setup manuals.
Value Delivered
The platform significantly boosted cancer diagnostic accuracy. By using AI to analyze real-time patient data, we were able to spot subtle patterns and biomarkers that indicate cancer progression.
Project Results
Our AI algorithms helped doctors craft treatment plans tailored to each individual’s unique condition, enhancing cure effectiveness.
By integrating with FHIR healthcare data standards, we ensured smooth information exchange, making data sharing seamless and efficient.
Our solution allowed oncologists to make better and quicker decisions and improve care outcomes.
The diagnostic accuracy, personalized treatments, and operational efficiency of our solution made it easy for stakeholders to justify their investment in AI tech.
Because we build FHIR applications within a cloud infrastructure, our solution can easily scale as healthcare needs change and technology advances.
