Beyond the AI Buzz: Pragmatic Applications of Big Data and AI in Population Health - Grand Rounds 3/9/23
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the pragmatic application of big data, advanced analytics, and AI in population health and social determinants of health in this informative grand rounds presentation by Dr. Jonathan Weiner, co-director for the Center for Population Health IT at Johns Hopkins School of Public Health. Delve into the distinctions between population health informatics, public health informatics, and clinical informatics. Examine the digital ecosystem surrounding healthcare and population health, emphasizing the crucial role of social determinants of health in human well-being. Investigate various data sources, applications, and contexts for social determinants of health and population health analytics. Gain insights into overlapping data science fields, including AI, machine learning, big data, and predictive analytics. Explore the pillars, processes, and target outcomes of a value-based learning health system, highlighting the importance of analytics and big data. Address the challenges of big data in population health, including volume, variety, velocity, and veracity. Compare the effectiveness of machine learning techniques with standard regression in predicting chronic care outcomes and costs. Learn about a study linking medical, public health, and human service databases to better predict opioid overdoses. Consider the potential biases and harms associated with AI and analytics in healthcare. Conclude by examining key data science-related challenges and opportunities in the field. Read more