Overview
Prescribing multiple medications simultaneously carries significant risks due to adverse drug-drug interactions (DDIs). Standard conflict detection systems often flag hundreds of minor warnings, leading to "alert fatigue" where doctors might accidentally ignore critical, life-threatening conflicts.
Intelligent Detection
This project approaches the problem using **Multi-Agent AI** and **Severity-Prioritized Search Algorithms**:
**Context-Aware Agents**: Instead of simple database lookups, the agents analyze patient profiles alongside the prescription list to contextually evaluate the risk of drug interactions.**Severity Prioritization**: The search algorithm is tuned to surface high-severity, contraindicating interactions first, suppressing low-priority noise so that healthcare providers can focus on what actually matters.**Prototype UI**: Deployed via Streamlit, allowing users to input a mock list of prescriptions and receive an instant, tiered breakdown of potential conflicts.Technical Stack
**Python**: Core logic and data processing.**AI/LLMs**: Intelligent agents utilized for nuanced understanding of drug interaction literature.**Streamlit**: Fast, responsive web interface for prototyping. 