Using Natural Language Processing to Identify Adverse Drug Events Characterized by Medication Replacement in Primary Care Electronic Medical Records: Algorithm and Validation Study
Background: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinical reasoning, and subtle indicators of health status. While health system research has traditionally relied upon structured data, natural language processing (NLP) enables the extraction of this rich textual information. Leveraging NLP could improve the identification and characterization of underreported adverse drug events (ADEs). Objective: The p
Record details
Published: 10 August 2026
Source: JMIR (Journal of Medical Internet Research)
Category: Research
Topics: Healthcare
Retrieved: 11 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
arXiv cs.AI · 10 August 2026
Towards Expert-level Medical AI for Real-time Video Consultations
arXiv cs.AI · 10 August 2026
Designing for Autonomous Motivation: Qualitative Interview Study on Pre-Enrollment Preferences of Survivors of Cancer for Digital Health Behavior Change Programs
JMIR (Journal of Medical Internet Research) · 10 August 2026
NIH limits funding for research on the health effects of public policy
Nature Machine Intelligence · 10 August 2026
MedPixel: A Unified Pixel-Language Model for Medical Reasoning and Segmentation
arXiv cs.AI · 10 August 2026
Intelligent Framework for Adverse Drug Event Identification Using Large Language Models and Retrieval-Augmented Generation: Development and Evaluation Study
JMIR (Journal of Medical Internet Research) · 10 August 2026
How to cite this record
ethics.ai (10 August 2026), “Using Natural Language Processing to Identify Adverse Drug Events Characterized by Medication Replacement in Primary Care Electronic Medical Records: Algorithm and Validation Study,” evidence record 18088, https://ethics.ai/record/18088 (originally published by JMIR (Journal of Medical Internet Research)).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.