Day 2 :
Better: A centre of complete living, Canada
Time : 09:15-09:50
Dr Shabnam Das Kar MD, FMNM is a consultant in Functional and Metabolic Medicine. She has a Fellowship in Metabolic and Nutritional Medicine from the American Academy of Anti-Aging Medicine, USA and a Brain Health Coaching Certification from Dr Daniel Amen’s Clinic, USA. Her medical practice is in India. She practices through telemedicine. In addition, she works as the Director of Medical Education, Better Medical Centre, Calgary, Alberta. She has co-founded the Metabolic Dietary Solutions Program (MDS Program), which is a program based on nutrition science and medicine. Dr Kar was practicing as an OBGY in India for more than 20 years before transitioning to Functional and Metabolic Medicine. She is an international speaker in her field. Her areas of interest are Autoimmune Diseases, Metabolic Dysfunction, Women and Cardiovascular Disease, Brain Fitness, Hormone Balance in Men and Women, Pre-Conception Counseling.
Polycystic Ovarian Syndrome (PCOS) is a major cause of menstrual irregularities, obesity, and infertility in women. The diagnosis of polycystic ovary syndrome (PCOS) is made if any two of the following three criteria are met: Androgen excess, ovulatory dysfunction, polycystic ovaries. Metabolic dysfunction (chronic low-grade inflammation, atherogenic dyslipidemia, insulin resistance, hypertension) is present in a large number of women with PCOS. Standard of care recommends lifestyle changes, such as diet and exercise, as first-line treatment for adolescent girls and women with PCOS. Oral contraceptives are recommended for women with menstrual irregularities. However, combined oral contraceptives may have deleterious effects on metabolism and lipid parameters in women with PCOS. Many women with PCOS have obesity, particularly central obesity. Weight loss in these women has been associated with better cycle control, higher ovulation rates, and improved cardiovascular risk factors. Though there is no consensus on the best diet for weight loss in women with PCOS, considering that insulin resistance is a major component of this condition, using a low carbohydrate diet can show better long-term benefits. Through my presentation, I will help practitioners add more tools to their toolkit. All these modalities help in dealing with the metabolic dysregulation of PCOS as well as fertility.
Alassane University Ouattara, Ivory Coast
ABE N’Doumy Noel holds a PhD in Sociology and Health Anthropology in 1993 from the University of Abidjan and a Doctorate of State in Human Sciences in 2008 from Alassane Ouattara University, Ivory Coast. He is the founder of the Research Laboratory on African Health Thought-Côte d'Ivoire (LARPAS-CI) and the Laboratory for Studies and Research in Reproductive Transition (LERTG). He is scientific director of the Department of Anthropology and Sociology at Alassane Ouattara University. He works with the Ministry of Health in Cote d'Ivoire on the Guinea Worm Eradication Program and the Malaria Control Program. His research focuses on environmental health, maternal health and health care in Africa.
The major question at the center of this study is the model for reading maternal and neonatal health problems in developing countries. On the subject, the demographic, epidemiological and statistical literature has accustomed us to a reading model based on observation and analysis at the micro-individual scale. The unit of analysis is the individual. This classic model of analysis, based on sociodemographic variables, has some effectiveness/relevance but is still limited. It appears partial and static. In contrast to this individualistic and fixed approach, we propose a dynamic and community-based observation scale that induces the concept of "reproductive transition". The reproductive transition is defined as the transition from a high-risk situation in a community to a lower-risk situation over a sustainable period in reproductive health. Indeed, the operational approach leads us to four types of expected results that are four possible trends of sociological evolution of this reproductive health. These expected results are: (a) The transition started; the problems are decreasing. (b) The stationary situation; there is neither growth nor decay. (c) The transition is mixed; some problems are growing, others are decreasing. (d) The alarming situation; all problems have an ascending pace. "Reproductive transition" thus appears as an innovative model for reading reproductive health problems. Its scale of observation is the community and not the individual. It thus constitutes a relevant health surveillance support for communities where maternal, neonatal and infant morbidity and mortality appear to be endemic.
University Teknikal Malaysia Melaka, Malaysia
Zuraida Abal Abas is currently a senior lecturer at the Department of Intelligent Computing & Analytics, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka. She obtained her PhD in Mathematics at Universiti Teknologi Malaysia; her MSc in Operational Research at London School of Economics, United Kingdom; and her BSc in Industrial Mathematics at Universiti Teknologi Malaysia. Her research interests are operational research, analytics, modeling and simulation.
The world population is increasing and continues to grow in the 21st century. It will be expected to reach 10 billion people in the year 2050 and 11 billion in the year 2088. Regardless of this number, the quality of life is one of the issues that need to be addressed and handle in an efficient way while facing the growing population phenomenon. One of the domains that are very related to the quality of life is health care service. It must be noted that the growing population will somehow create new and lasting challenges for healthcare worldwide. In order to face these challenges, the emerging digital technology such as machine learning, cloud computing, Artificial Intelligence and Internet of Things (IoT) should be utilized in which massive expansion of data is available through this technology. These data are then transformed into actionable insight through Analytics, the scientific process that uses mathematics, statistics, predictive modeling and machine learning techniques. This paper provides a brief review and discussion on IoT Healthcare Analytics for innovations of healthcare and nursing in the challenges of a growing population. A comparison of IoT for various healthcare applications such as remote health monitoring, fitness programs, chronic diseases and elderly care as well as the analytics techniques for the huge volume of health information is presented in the study. The challenges of the implementation are also discussed. The impact of this study is to improve the healthcare system using the new dimension of affordable, practical and easy-to-use technology for innovative healthcare solution.