Expanding the Boundaries of Health Informatics Using Artificial Intelligence
Papers from the 2013 AAAI Workshop
Martin Michalowski, Wojtek Michalowski, Dympna O'Sullivan, Szymon Wilk, Workshop Cochairs
The rapid development and expansion of health informatics is demonstrated by the proliferation of electronic patient records and the transition to computer-based patient treatment tools and point-of-care informatics infrastructure. Accelerating its growth is the increasing availability of medical information such as evidence-based clinical guidelines and results of clinical studies including randomized control trials. Unfortunately, the rate of growth combined with improved data availability leads to health information overload that can severely impair clinical work and adversely affect health-related decision-making. AI techniques are very well suited to help overcome this problem and can facilitate advances in the health informatics area that can have a profound effect on patient outcomes. As such, a true opportunity exists to shape the future of healthcare systems through the application of AI to address a number of emerging health system problems.
AI techniques can help not only with collecting, organizing and storing volumes of personal and population data (including sensitive patient information), but also with analyzing data and information with the purpose of facilitating data-driven and evidence-based decision making. The latter can be achieved by identifying and presenting health practitioners with pertinent medical information and knowledge when it is needed. Challenges lie in both determining what is relevant medically and contextually, and when and in it what form it is appropriate to provide this information and knowledge. For example, presenting disease- and treatment-relevant information to a physician at the point of care during a patient encounter enables the development of decision support tools that lead to improved patient outcomes and has a positive societal impact. Developing (and deploying) intelligent health systems is a research area ripe for AI techniques where advances are needed to tackle real-world healthcare problems such as disease identification and management, drug-drug and drug-disease interaction, and patient education.