Rational Drug Use Support System: design, artificial intelligence integration, and pilot feasibility trial.
8 affiliations
- 1Türkiye Public Health and Chronic Diseases Institute - Istanbul, Türkiye.
- 2Mersin University, Mersin Medical School, Department of Internal Medicine, Division of Geriatrics - Mersin, Türkiye.
- 3Türkiye Health Data Research and Artificial Intelligence Applications Institute - Istanbul, Türkiye.
- 4Istanbul University, Istanbul Faculty of Medicine - Istanbul, Türkiye.
- 5Istanbul Gelisim University, Faculty of Engineering and Architecture, Department of Software Engineering - Istanbul, Türkiye.
- 6Istanbul University-Cerrahpasa, Department of Computer Engineering - Istanbul, Türkiye.
- 7Istanbul University, Department of Computer Engineering - Istanbul, Türkiye.
- 8Istanbul University, Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Geriatrics - Istanbul, Türkiye.
Abstract
Objective
The Rational Drug Use Support System was developed to assist patients in using the right drug, at the right time and at the right dose according to their treatment protocols. The aim of this study was to evaluate the performance of an artificial intelligence-enhanced mobile application designed to support rational drug use and to assess its feasibility and usability through a pilot trial.Methods
The system includes an artificial intelligence -powered mobile application and a web-based interface integrating convolutional neural networks and object detection algorithms for human activity recognition. To build an image library, real patient videos were recorded in a hospital setting under physician supervision. A total of 357 original medication-intake videos were collected from 31 patients, which were then segmented into 1,626 short clips to train the artificial intelligence model. The system was first tested under controlled laboratory conditions and then evaluated for feasibility in a hospital pilot trial involving eight participants over 15 days.Results
The proposed artificial intelligence model achieved 94% accuracy in recognizing medication intake activities in the test set, suggesting promising performance that warrants further evaluation. Exploratory analyses of the 36-Item Short Form Health Survey Questionnaire administered to patients who utilized the mobile application for 15 days revealed improvements in the domains of social functioning, vitality, and mental health.Conclusion
The findings suggest that the "Rational Drug Use Support System" appears feasible for implementation in telemedicine and clinical settings to support rational drug use and patient engagement in chronic disease management. However, larger controlled studies are warranted to confirm these preliminary findings.
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BibTeX
@article{kahraman2026rational,
title = {{Rational Drug Use Support System: design, artificial intelligence integration, and pilot feasibility trial.}},
author = {Mustafa Kahraman and Meris Esra Bozkurt and Soner Kotan and Buse Nur Ozturk and Rana Aydın and Saim Hatipoğlu and Hasan Ali Eris and Mehmet Ali Erturk and Muhammed Ali Aydin and Mehmet Akif Karan},
journal = {Revista da Associacao Medica Brasileira (1992)},
year = {2026},
month = oct,
doi = {10.1590/1806-9282.20260803},
url = {https://europepmc.org/article/MED/42912069},
note = {CC BY},
}
RIS
TY - JOUR
TI - Rational Drug Use Support System: design, artificial intelligence integration, and pilot feasibility trial.
AU - Mustafa Kahraman
AU - Meris Esra Bozkurt
AU - Soner Kotan
AU - Buse Nur Ozturk
AU - Rana Aydın
AU - Saim Hatipoğlu
AU - Hasan Ali Eris
AU - Mehmet Ali Erturk
AU - Muhammed Ali Aydin
AU - Mehmet Akif Karan
PY - 2026
DA - 2026/10/16
JO - Revista da Associacao Medica Brasileira (1992)
DO - 10.1590/1806-9282.20260803
UR - https://europepmc.org/article/MED/42912069
AB - Objective The Rational Drug Use Support System was developed to assist patients in using the right drug, at the right time and at the right dose according to their treatment protocols. The aim of this study was to evaluate the performance of an artificial intelligence-enhanced mobile application designed to support rational drug use and to assess its feasibility and usability through a pilot trial.Methods The system includes an artificial intelligence -powered mobile application and a web-based interface integrating convolutional neural networks and object detection algorithms for human activity recognition. To build an image library, real patient videos were recorded in a hospital setting under physician supervision. A total of 357 original medication-intake videos were collected from 31 patients, which were then segmented into 1,626 short clips to train the artificial intelligence model. The system was first tested under controlled laboratory conditions and then evaluated for feasibility in a hospital pilot trial involving eight participants over 15 days.Results The proposed artificial intelligence model achieved 94% accuracy in recognizing medication intake activities in the test set, suggesting promising performance that warrants further evaluation. Exploratory analyses of the 36-Item Short Form Health Survey Questionnaire administered to patients who utilized the mobile application for 15 days revealed improvements in the domains of social functioning, vitality, and mental health.Conclusion The findings suggest that the "Rational Drug Use Support System" appears feasible for implementation in telemedicine and clinical settings to support rational drug use and patient engagement in chronic disease management. However, larger controlled studies are warranted to confirm these preliminary findings.
SN - 0104-4230
SN - 1806-9282
ER -