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Condition: Atrial Fibrillation
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Total 389 results found since Jan 2013.

Improving Anticoagulant Treatment Strategies of Atrial Fibrillation Using Reinforcement Learning
AMIA Annu Symp Proc. 2021 Jan 25;2020:1431-1440. eCollection 2020.ABSTRACTIn this paper, we developed a personalized anticoagulant treatment recommendation model for atrial fibrillation (AF) patients based on reinforcement learning (RL) and evaluated the effectiveness of the model in terms of short-term and long-term outcomes. The data used in our work were baseline and follow-up data of 8,540 AF patients with high risk of stroke, enrolled in the Chinese Atrial Fibrillation Registry (CAFR) study during 2011 to 2018. We found that in 64.98% of patient visits, the anticoagulant treatment recommended by the RL model were conc...
Source: AMIA Annual Symposium Proceedings - May 3, 2021 Category: Bioinformatics Authors: Lei Zuo Xin Du Wei Zhao Chao Jiang Shijun Xia Liu He Rong Liu Ribo Tang Rong Bai Jianzeng Dong Xingzhi Sun Gang Hu Guotong Xie Changsheng Ma Source Type: research

Long-term oral anticoagulation for atrial fibrillation in low and middle income countries
Discussions regarding oral anticoagulation (OAC) use in low and middle income countries (LMICs) have historicallybeendominated by severallong-held beliefs. The first is that the quality of vitamin K antagonist (VKA) based anticoagulation is poor in these countries. The veracity of this assumption is supported by a large number of studies documenting both lower prescription of OACs, and a lower proportion of international normalised ratio (INR) values in the therapeutic range.1The second is that a large proportion of patients receiving OAC in LMICs have atrial fibrillation (AF) related to valvular heart disease, and rheumat...
Source: Indian Heart J - April 18, 2021 Category: Cardiology Authors: Venkatakrishnan Ramakumar Alexander P Benz Ganesan Karthikeyan Source Type: research