Pharmacy Expert System for Medication Guidance
Educating patients about medication intake, dosage, and potential side effects is crucial to enhance medication safety and adherence. Misunderstandings due to language barriers or insufficient communication can lead to medication misuse, adverse drug reactions, and potentially dangerous drug interactions.
Research Project
We are developing an interactive expert system application powered by Large Language Models, designed specifically for pharmacy clients to obtain reliable, personalized information about their medications. The expert system provides clear explanations regarding medication usage, effects, and interactions, tailored to individual patient needs. Its ability to reformulate explanations in multiple ways significantly enhances understanding, thereby increasing patient safety and reducing risks associated with incorrect medication use or interactions. Available 24/7, the expert system offers continuous support, bridging language gaps and improving the overall medication management experience for patients. Importantly, the expert system strictly utilizes a validated knowledge base, ensuring only verified and accurate pharmaceutical information is provided to users.
Tags :
Related Posts
A Python Toolbox for Connectome-Based Predictive Modeling
Confound-Corrected Connectome-Based Predictive Modelling is a Python package for performing connectome-based predictive modeling (CPM).
Read MoreCertification for Medical Machine Learning
This project aims to identify regulatory requirements for the use and certification of machine learning algorithms for medical devices.
Read MoreReMap: Remote Monitoring in Psychiatry
Together with Prof. Dr. Nils Opel from the Department of Psychiatry and Psychotherapy at Jena University Hospital, we aim to advance mental health research and improve the lives of individuals with mental disorders.
Read More