Accelerating medical recommendations preparation

Development of an AI-driven solution for analyzing contraindications and providing psychedelic medicine recommendations, streamlining the decision-making process

Industry:
Therapy
Country:
United States

Client

Entrepreneur and author of articles and books on the subject of psychedelic medicines and their use in treatment

Business challenges

  • Complex process of preparing medical reports
  • Lack of a centralized solution for processing EHR and preparing personal recommendations

Our solutions

  • AI implementation
  • UI for medical professionals and consumers
  • Admin panel for managing master data

Project implementation

We began by developing a proof of concept (PoC) that utilized AI to analyze electronic health records (EHR) and generate recommendations for psychedelic medications. Our engineering team partnered with the R&D division to rigorously test and fine-tune the algorithms and models, ensuring we selected the most effective solution.

We built a robust architecture using TypeScript, Node.js, and Express.js. This setup facilitated efficient data processing and seamless integration with AWS services and Redis for real-time data handling. Our system leveraged AWS Bedrock for AI-driven analysis and bullMQ for job scheduling, ensuring high performance and reliability.

The frontend was developed using React, axios, and antd, creating a dynamic and responsive user interface for both medical professionals and patients. Sass was employed for advanced styling, allowing for a visually appealing and highly usable interface. Alsom, for managing master data and user permissions we developed the admin panel.

This modular approach enabled us to develop a highly flexible and scalable solution, easily integrated into any infrastructures and adaptable to future technological advancements.

Technology stack

  • Typescript
  • Node.js
  • React
  • Express.js
  • AWS, AWS Bedrock
  • bullMQ
  • Redis
  • PostgreSQL

Key activities

Business outcomes

The implementation of the new web application and AI technology resulted in significant improvements for medical professionals and the reporting process:

  1. Reduced the time required to prepare medical reports by 30%
  2. Provided a unified platform for processing Electronic Health Records (EHR) and generating personalized recommendations, enhancing data management and accessibility
  3. Leveraged AI-driven analysis to deliver more accurate contraindications and medicine recommendations, improving the quality of patient care
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