1,722,357 research outputs found
My-Linh Nguyen Luong's Quick Files
No full textThe Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity
Using behaviour change theory to understand and promote physical activity in adults with chronic lower limb joint pain
No full text© 2024 My Linh Nguyen LuongAlthough guidelines recommend physical activity for people with osteoarthritis, most people with osteoarthritis do not meet the recommended levels of physical activity necessary to achieve positive health benefits. This thesis uses behaviour change theory to:
- assess integrated dual-process models, including associations between physical activity and non-conscious process of physical activity (prospective study);
- evaluate effectiveness of financial incentives to motivate physical activity (systematic review and meta-analysis, plus a narrative case study);
-determine patient preferences for physical activity rewards programs (discrete choice experiment).
Findings can inform development of physical activity programs for people with osteoarthritis
Emerging Advancement of Data Science in the Healthcare Informatics
No full textThe healthcare domain is experiencing a massive transition, driven by the threefold target of increased efficiency, reduced costs and positive results for patients. The lack of clinical experience impact can largely be due to inadequate statistical model effectiveness, difficulties understanding dynamic model forecasts, and lack of evidence from prospective clinical trials that have a strong benefit over the standard of treatment. In this article, the promise of personalized medicine's state-of-the-art data science methods, discussing open barriers, and Highlight paths that might in the future help to solve them. We should anticipate many shifts in future medical informatics science in view of the fluid existence of many of the driving factors behind advancement in knowledge management methods and their technology, developments in medicine and health care, and the constantly shifting demands, requirements and aspirations of human populations. This chapter gives brief explanation for relevance of the applications of predictive analytics strategies and importance of data science in healthcare.</p
sj-docx-4-npx-10.1177_1934578X221128410 - Supplemental material for Discriminative Chemical Profiles of Shan Tuyet Tea (<i>Camellia sinensis</i> var. Shan) and Sinensis Tea (<i>Camellia sinensis</i> var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity
No full textSupplemental material, sj-docx-4-npx-10.1177_1934578X221128410 for Discriminative Chemical Profiles of Shan Tuyet Tea (Camellia sinensis var. Shan) and Sinensis Tea (Camellia sinensis var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity by Kieu-Oanh Thi Nguyen, Phuong-Linh Nguyen and
Hoang-Long Le, Huyen-Thao Le in Natural Product Communications</p
sj-png-1-npx-10.1177_1934578X221128410 - Supplemental material for Discriminative Chemical Profiles of Shan Tuyet Tea (<i>Camellia sinensis</i> var. Shan) and Sinensis Tea (<i>Camellia sinensis</i> var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity
No full textSupplemental material, sj-png-1-npx-10.1177_1934578X221128410 for Discriminative Chemical Profiles of Shan Tuyet Tea (Camellia sinensis var. Shan) and Sinensis Tea (Camellia sinensis var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity by Kieu-Oanh Thi Nguyen, Phuong-Linh Nguyen and
Hoang-Long Le, Huyen-Thao Le in Natural Product Communications</p
sj-docx-2-npx-10.1177_1934578X221128410 - Supplemental material for Discriminative Chemical Profiles of Shan Tuyet Tea (<i>Camellia sinensis</i> var. Shan) and Sinensis Tea (<i>Camellia sinensis</i> var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity
No full textSupplemental material, sj-docx-2-npx-10.1177_1934578X221128410 for Discriminative Chemical Profiles of Shan Tuyet Tea (Camellia sinensis var. Shan) and Sinensis Tea (Camellia sinensis var. sinensis) Collected in Ta Xua, Son La, Vietnam and Their Correlation With Antioxidant Activity by Kieu-Oanh Thi Nguyen, Phuong-Linh Nguyen and
Hoang-Long Le, Huyen-Thao Le in Natural Product Communications</p
A Value of Data Science in the Medical Informatics: An Overview
No full textThe use of data science and predictive modelling for real-time clinical decision making is increasingly recognized. The initial step in the path towards the adoption of real-time prediction and forecast is the creation and evaluation of predictive models for clinical practice. Training in medical informatics is not only necessary for medical students but also for all medical personnel at all technical levels of education. A critical move required for the learning and application of clinical medicine is to incorporate medical informatics into the broad scope of medical informatics. Current major fields of research can be categorized according to the organization, implementation, assessment, representation, and interpretation of medical information. We should expect many changes in medical informatics, because of many of the driving forces behind advancement in information management methods and their innovations, developments in medicine and health care, and the constantly evolving needs, requirements and aspirations of human societies. Data science and predictive analytics offer distinct methodologies for tapping vast data sets of medical knowledge from intelligence. These approaches have many possibilities, such as identifying patterns, forecasting outcomes, and optimizing algorithms better. But medical data collection and management often faces few problems, such as data size, data consistency, durability and data completeness. This research offers an extensive overview of medical data processing, predictive analytics and data science in order to contribute to the area of medical informatics and data science. It offers explanations of basic principles using data science in the evolving field of medical informatics. Also the research includes review of benefits, applications and future of data science in healthcare.</p
Potential and Adoption of Data Science in the Healthcare Analytics
No full textThe creation and validation of clinical practice predictive models is just the initial step in the path towards mainstream adoption of predictions for real-time point-of-care. Adoption of healthcare analytics can occur at diverse levels, including medical error tracking and avoidance, data integration, predictive analysis and personalized modelling. Although substantial advancement and progress has been made from the perspective of data science and study, challenges and opportunities remain. Current main fields of study can be categorized according to the organisation, introduction, and assessment of health information systems, patient information representation, and analysis and interpretation of underlying signals and data. We should anticipate many shifts in future medical informatics science in view of the fluid existence of many of the driving factors behind advancement in knowledge management methods and their technology, developments in medicine and health care, and the constantly shifting demands, requirements and aspirations of human populations. This chapter will explain the relevance of the application of predictive analytics strategies focused on data science in healthcare. By way of intelligent process analysis and medical data mining, the device would be able to derive real time valuable information that aids in decision making and medical tracking.</p
Eminent Role of Machine Learning in the Healthcare Data Management
No full textThe large quantities of data that can be produced in the medical sector. Each healthcare institution has its own patient records that include important details. When correctly evaluated, the healthcare domain will produce value from this data. A critical step necessary for the learning and application of clinical medicine is to bring medical informatics into the broad scope of medical education. Current main research areas can be categorized according to the organisation, introduction, and assessment of health information systems, the representation of medical expertise, and the study and interpretation of underlying signals and evidence. Machine learning has become really popular in the last few decades, and different methods of machine learning have been developed. It concentrates on the analyzing, developing, designing and implementing of techniques. The algorithms for machine learning use a well-defined learning method that best fits the purpose of the medical data analytics. Simple principles of the healthcare sector and machine learning will be defined in this study. The chapter shows how data analytics and machine learning can assist in the healthcare process, also posing certain obstacles, possibilities that need to be explored in order to achieve successful analytics in healthcare diagnosis.</p
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