AI-driven detection of adverse drug events in electronic health records of older adults

Description

Adverse drug events (ADEs) are a major cause of morbidity, hospitalizations and reduced quality of life in patients. Yet, ADEs are frequently under recognized in clinical practice, especially when they are written down in free-text electronic health records (EHRs).
A novel approach to overcome this, is with the use of a knowledge-augmented AI tool. This tool integrates natural language processing (NLP) with pharmacological knowledge and patient records to identify medication-related harm.
The aim is to support healthcare professionals to detect ADEs in an earlier stadium and thereby improving medication safety and reduce hospitalization.

Who is the principal investigator?

Prof. Dr. Fatma Karapinar- Çarkit

Team

Noa van der Ploeg, MSc
Dr. Yannick Nielen
Dr. Judith de Ruijter-van Dalem
Dr. Sander Puts (Maastro Clinic/UM)

Contact for internship or collaboration

Dr. Yannick Nielen (yannick.nielen@mumc.nl)
Dr. Judith de Ruijter-van Dalem (judith.van.dalem@mumc.nl)
Also, visit our Vacancies page.

Contact for general questions

Noa van der Ploeg (noa.ploeg@mumc.nl)

Was this page useful?

Good

Sufficient

Insufficient

To help us improve our website we would like to know why you do not find this page useful. You can select more than one reason below and give your opinion.

I find the page too difficult to understand

I can\'t find what I am looking for

I find that the page is too boring

Other reason (fill in below)

Your opinion

Geef uw mening over de website, of vertel ons hoe wij onze website kunnen verbeteren.

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.