English
norskBlar i forfatter "Ngo, Phuong"
Viser treff 1-7 av 7
-
Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-06)There is a large proliferation of complex data-driven artificial intelligence (AI) applications in many aspects of our daily lives, but their implementation in healthcare is still limited. This scoping review takes a theoretical approach to examine the barriers and facilitators based on empirical data from existing implementations. We searched the major databases of relevant scientific publications ... -
Challenges and opportunities beyond structured data in analysis of electronic health records
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-14)Electronic health records (EHR) contain a lot of valuable information about individual patients and the whole population. Besides structured data, unstructured data in EHRs can provide extra, valuable information but the analytics processes are complex, time-consuming, and often require excessive manual effort. Among unstructured data, clinical text and images are the two most popular and important ... -
Control of Blood Glucose for Type-1 Diabetes by Using Reinforcement Learning with Feedforward Algorithm
(Journal article; Tidsskriftartikkel; Peer reviewed, 2018-12-30)<p><i>Background</i>: Type-1 diabetes is a condition caused by the lack of insulin hormone, which leads to an excessive increase in blood glucose level. The glucose kinetics process is difficult to control due to its complex and nonlinear nature and with state variables that are difficult to measure.</p> <p><i>Methods</i>: This paper proposes a method for automatically calculating the basal and ... -
Data-Driven Robust Control Using Reinforcement Learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-21)This paper proposes a robust control design method using reinforcement learning for controlling partially-unknown dynamical systems under uncertain conditions. The method extends the optimal reinforcement learning algorithm with a new learning technique based on the robust control theory. By learning from the data, the algorithm proposes actions that guarantee the stability of the closed-loop system ... -
Food recommendation using machine learning for physical activities in patients with type 1 diabetes
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019)Physical activities have a significant impact on blood glucose homeostasis of patients with type 1 diabetes. Regular physical exercise provides many proven health benefits and is recommended as part of a healthy lifestyle. However, one of the main side effects of physical activities is hypoglycemia (low blood glucose). Fear of hypoglycemia generally leads to the patients not participating in ... -
Machine Learning in Chronic Pain Research: A Scoping Review
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-02)Given the high prevalence and associated cost of chronic pain, it has a significant impact on individuals and society. Improvements in the treatment and management of chronic pain may increase patients’ quality of life and reduce societal costs. In this paper, we evaluate state-of-the-art machine learning approaches in chronic pain research. A literature search was conducted using the PubMed, IEEE ... -
Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-12)<p><i>Background.</i> Since physical activity has a high impact on patients with type 1 diabetes and the risk of hypoglycemia (low blood glucose levels) is significantly higher during and after physical activities, an automatic method to provide a personalized recommendation is needed to improve the blood glucose management and harness the benefits of physical activities. This paper aims to reduce ...
