ArticleScientific reports2021
Development of a system to support warfarin dose decisions using deep neural networks.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.Current topics in medicinal chemistry · 2025Pooled it
- Narrow Therapeutic Index Drugs: Regulatory Frameworks, Bioequivalence, and Model-Informed Precision Dosing.Pharmaceutics · 2026Review
- Accelerated drug development using a digital formulator and a self-driving tableting data factory.Nature communications · 2026Article
- Artificial intelligence and machine learning for precision warfarin dosing: a comprehensive narrative review.European journal of clinical pharmacology · 2026Review
- Building the next frontier: Artificial intelligence in 3D-printed medicines.Biomaterials translational · 2026Review
- Advancing Drug Discovery with AI: Machine and Deep Learning Strategies for Target Identification and Precision Nanomedicine.International journal of nanomedicine · 2026Review
- Machine Learning for Warfarin Therapy: A Systematic Review.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Artificial intelligence in cardiovascular pharmacotherapy: applications and perspectives.European heart journal · 2025Review
- Artificial intelligence guided dosing decisions: a qualitative study on health care provider perspectives.BMJ health & care informatics · 2025Article
- The impact of artificial intelligence on biomarker discovery.Emerging topics in life sciences · 2025Article
- A Prediction Model of Stable Warfarin Doses in Patients After Mechanical Heart Valve Replacement Based on a Machine Learning Algorithm.Reviews in cardiovascular medicine · 2025Article
- Artificial Intelligence in Atrial Fibrillation: From Early Detection to Precision Therapy.Journal of clinical medicine · 2025Review
- Anticoagulation Management: Current Landscape and Future Trends.Journal of clinical medicine · 2025Review
- Artificial intelligence and atrial fibrillation: A bibliometric analysis from 2013 to 2023.Heliyon · 2024Review
- Optimizing warfarin dosing for patients with atrial fibrillation using machine learning.Scientific reports · 2024Article
- Article
- Revolutionizing healthcare: the role of artificial intelligence in clinical practice.BMC medical education · 2023Review
- Optimizing the dynamic treatment regime of in-hospital warfarin anticoagulation in patients after surgical valve replacement using reinforcement learning.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data.Frontiers in cardiovascular medicine · 2022Article
- Artificial intelligence in modern clinical practice (Review).Medicine internationalReview
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 19,719 inpatients from three institutions was analyzed. The PT INR prediction algorithm included dense and recurrent neural networks, and was designed to predict the 5th-day PT INR from data of days 1-4. Data from patients in one hospital (n = 22,314) was used to train the algorithm which was tested with the datasets from the other two hospitals (n = 12,673). The performance of 5th-day PT INR prediction was compared with 2000 predictions made by 10 expert physicians. A generator of individualized warfarin dose-PT INR tables which simulated the repeated administration of varying doses of warfarin was developed based on the prediction model. The algorithm outperformed humans with accuracy terms of within ± 0.3 of the actual value (machine learning algorithm: 10,650/12,673 cases (84.0%), expert physicians: 1647/2000 cases (81.9%), P = 0.014). In the individualized warfarin dose-PT INR tables generated by the algorithm, the 8th-day PT INR predictions were within 0.3 of actual value in 450/842 cases (53.4%). An artificial intelligence-based warfarin dosing algorithm using a recurrent neural network outperformed expert physicians in predicting future PT INRs. An individualized warfarin dose-PT INR table generator which was constructed based on this algorithm was acceptable.
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