ML-powerd Drugs Interaction analysis
Drug interaction checker enabling providers to quickly and accurately assess potential drug interactions for safer patient care
Challenge
Integrate AI/ML-powered features into an existing healthcare platform to enable healthcare providers to efficiently check for potential drug interactions. This involves developing a system that analyzes patient data from the platform’s database and identifies possible interactions between prescribed medications, enhancing the accuracy of treatment plans and ensuring patient safety.
Solution
To address the need for efficient drug interaction checking within the healthcare platform, we implemented an advanced solution involving the integration of a comprehensive drug database and the development of a custom-trained machine learning (ML) model. This model is specifically designed to handle the vast and complex data associated with numerous drugs, their interactions, and potential side effects.
ML Development and API Integration
The ML model was developed using a deep learning approach, trained on extensive datasets that include drug interaction records, clinical trials, and pharmacological research. The model can analyze patient data in real-time, identifying potential interactions between prescribed medications with high accuracy. It also learns and improves over time as it processes more data, ensuring that healthcare providers receive the most up-to-date and relevant information.
We integrated the model into the existing healthcare platform through a robust API, designed to seamlessly connect with the current system with minimal changes to the user interface (UI). This ensures that healthcare providers can easily access the new feature without needing to navigate a completely new system, preserving the workflow they are accustomed to.
To further enhance the solution, we integrated ChatGPT to provide contextual support. This integration allows providers to engage in conversational queries regarding drug interactions, receive explanations, and explore alternative treatment options in a user-friendly manner. ChatGPT’s natural language processing capabilities complement the ML model by offering insights and clarifications, ensuring that providers have a comprehensive understanding of the interaction data.
The result
The developed solution not only streamlines the drug interaction checking process but also enhances the platform’s overall functionality, making it a powerful tool for improving patient safety and care.
Technologies
API Integration
RESTful API, GraphQL
Backend
Node.js, Python,
TensorFlow
Project team:
ML-Engineer
DevOps
Project Duration:
Completed in 8 weeks
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