Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Assessing the ability of GPT-4o to visually recognize medications and provide patient education
11
Zitationen
2
Autoren
2024
Jahr
Abstract
Various studies have investigated the ability of ChatGPT (OpenAI) to provide medication information; however, a new promising feature has now been added, which allows visual input and is yet to be evaluated. Here, we aimed to qualitatively assess its ability to visually recognize medications, through medication picture input, and provide patient education via written and visual output. The responses were evaluated by accuracy, precision and clarity using a 4-point Likert-like scale. In regards to handling visual input and providing written responses, GPT-4o was able to recognize all 20 tested medications from packaging pictures, even with blurring, retrieve their active ingredients, identify formulations and dosage forms and provide detailed, yet concise enough, patient education in an almost completely accurate, precise and clear manner with a score of 3.55 ± 0.605 (85%). In contrast, the visual output through GPT-4o generated images illustrating usage instructions contained many errors that would either hinder the effectiveness of the medication or cause direct harm to the patient with a poor score of 1.5 ± 0.577 (16.7%). In conclusion, GPT-4o is capable of identifying medications from pictures and exhibits contrasting patient education performance between written and visual output with very impressive and poor scores, respectively.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.245 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.102 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.468 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.429 Zit.