Artificial Intelligence in the Healthcare Sector

Julia M. Puaschunder, Dieter Feierabend

Abstract


To an extent as never before in the history of medicine, computers are supporting human input, decision making and provision of data.  In today’s healthcare sector and medical profession, AI, algorithms, robotics and big data are used to derive inferences for monitoring large-scale medical trends, detecting and measuring individual risks and chances based on data-driven estimations. A knowledge-intensive industry like the healthcare profession highly depends on data and analytics to improve therapies and practices. In recent years, there has been tremendous growth in the range of medical information collected, including clinical, genetic, behavioral and environmental data. Every day, healthcare professionals, biomedical researchers and patients produce vast amounts of data from an array of devices. These include electronic health records (EHRs), genome sequencing machines, high-resolution medical imaging, smartphone applications and ubiquitous sensing, as well as Internet of Things (IoT) devices that monitor patient health (OECD 2015). Through machine learning algorithms and unprecedented data storage and computational power, AI technologies have most advanced abilities to gain information, process it and give a well-defined output to the end-user.  Daily monitoring thereby aids to create big data to recognize behavioral patterns’ relation to health status in order to create predictions with highest mathematical precision based on big data capturing large-scale samples. AI thereby enlightens to analyze the relation between prevention and treatment and patient outcomes in all stages of diagnosis, treatment, drug development and monitoring, personalized medicine, patient control and care.  Advanced hospitals are looking into AI solutions to support and perform operational initiatives that increase precision and cost effectiveness.  Robotics have been used for disabled and patient care assistance.  Medical decision making has been supported through predictive analytics and general healthcare management technology. Network connectivity allows access to affordable healthcare around the globe in a cost-effective way.  


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