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Computer-Assisted Diagnosis: Diabetes and Cardiovascular Risk brings together the multi-faceted information about the research and clinical application academic, clinical, bioengineering, and bioinformatics perspectives. The editors bring together a stellar diverse case of authors to pull together this diverse and interesting field. Academic researchers, bioengineers, new investigators, and students interested in diabetes and heart disease need an authoritative reference to bring this multidisciplinary field together to reduce the amount of time spent on source-searching and more time on actual research and the clinical application. This reference accomplishes this with contributions by authors from around the world.
- Provides valuable information for academic clinicians, researchers, bioengineers, and industry on diabetes and cardiovascular disease
- Discusses the impact of diabetes on cardiovascular disease
- Covers statistical classification techniques and risk stratification
Diabetes researchers, endocrinology/cardiovascular researchers; bioengineers, and bioinformatics and imaging scientists interested in diabetes
- Impact of Diabetes on Cardiovascular Disease
2. Statistical Classification Techniques for Risk Stratification of Pima Diabetic Data
3. The role of PKCβ in diabetes mellitus-accelerated atherosclerosis
4. Cardiovascular risk factors in diabetes: Focus on hypoglycemia, dyslipidemia, weight and cardiovascular disease
5. Effect on myocardial ischemia reperfusion injury in type 2 diabetes
6. Hypertension in diabetes and the risk of cardiovascular disease
7. Diabetes-mediated myelopoiesis and the relationship to cardiovascular risk
8. Getting to the "Heart" of the Matter on Diabetic Cardiovascular Disease
9. Gender and diabetes mellitus in the coronary heart disease risk
10. Synergistic and Non-synergistic Associations for Cigarette Smoking and Non-tobacco Risk Factors for Cardiovascular Disease Incidence
11. Diabetes treatments and risk of heart failure, cardiovascular disease, and all-cause mortality
12. Implication of Median-based approaches for missing value and outlier removal to improve the machine learning performance in Pima Diabetic Data
- No. of pages:
- © Elsevier 2020
- 1st June 2020
- Paperback ISBN:
Dr. Ayman El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master's degrees in electrical engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. He has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 publications including 105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents.
Professor, University Scholar and Chair, Bioengineering Department, University of Louisville, KY, USA
Dr. Jasjit Suri, PhD, MBA, Fellow AIMBE is an innovator, visionary, scientist, and internationally known world leader. Dr. Suri received the Director General’s Gold medal in 1980 and the Fellow of American Institute of Medical and Biological Engineering, awarded by the National Academy of Sciences, Washington DC, in 2004. He has published over 650 peer-reviewed articles and has over 100 innovations and trademarks. He has author or co-authored over 45 books. He is currently Chairman of Global Biomedical Technologies, Inc., Roseville, CA, and is on the board of AtheroPoint, Roseville, CA, a company dedicated to atherosclerosis imaging for early screening for stroke and cardiovascular monitoring. He has held positions as a chairman of IEEE Denver section and advisor board member to healthcare industries and several universities in USA and abroad.
Chairman of Global Biomedical Technologies, Inc., Roseville, CA, USA