Chapter title |
Systems Health: A Transition from Disease Management Toward Health Promotion
|
---|---|
Chapter number | 9 |
Book title |
Healthcare and Big Data Management
|
Published in |
Advances in experimental medicine and biology, January 2017
|
DOI | 10.1007/978-981-10-6041-0_9 |
Pubmed ID | |
Book ISBNs |
978-9-81-106040-3, 978-9-81-106041-0
|
Authors |
Li Shen, Benchen Ye, Huimin Sun, Yuxin Lin, Herman van Wietmarschen, Bairong Shen |
Abstract |
To date, most of the chronic diseases such as cancer, cardiovascular disease, and diabetes, are the leading cause of death. Current strategies toward disease treatment, e.g., risk prediction and target therapy, still have limitations for precision medicine due to the dynamic and complex nature of health. Interactions among genetics, lifestyle, and surrounding environments have nonnegligible effects on disease evolution. Thus a transition in health-care area is urgently needed to address the hysteresis of diagnosis and stabilize the increasing health-care costs. In this chapter, we explored new insights in the field of health promotion and introduced the integration of systems theories with health science and clinical practice. On the basis of systems biology and systems medicine, a novel concept called "systems health" was comprehensively advocated. Two types of bioinformatics models, i.e., causal loop diagram and quantitative model, were selected as examples for further illumination. Translational applications of these models in systems health were sequentially discussed. Moreover, we highlighted the bridging of ancient and modern views toward health and put forward a proposition for citizen science and citizen empowerment in health promotion. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 34 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 5 | 15% |
Researcher | 5 | 15% |
Student > Ph. D. Student | 4 | 12% |
Student > Bachelor | 2 | 6% |
Lecturer | 2 | 6% |
Other | 4 | 12% |
Unknown | 12 | 35% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 3 | 9% |
Agricultural and Biological Sciences | 3 | 9% |
Medicine and Dentistry | 3 | 9% |
Social Sciences | 2 | 6% |
Nursing and Health Professions | 1 | 3% |
Other | 8 | 24% |
Unknown | 14 | 41% |