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Health intelligence: how artificial intelligence transforms population and personalized health
Arash Shaban-Nejad1, Martin Michalowski2, David L Buckeridge3
11Department of Pediatrics, University of Tennessee Health Science Center - Oak Ridge National Laboratory (UTHSC-ORNL) Center for Biomedical Informatics, Memphis, TN USA.
Abstract:
Advances in computational and data sciences for data management, integration, mining, classification, filtering, visualization along with engineering innovations in medical devices have prompted demands for more comprehensive and coherent strategies to address the most fundamental questions in health care and medicine. Theory, methods, and models from artificial intelligence (AI) are changing the health care landscape in clinical and community settings and have already shown promising results in multiple applications in healthcare including, integrated health information systems, patient education, geocoding health data, social media analytics, epidemic and syndromic surveillance, predictive modeling and decision support, mobile health, and medical imaging (e.g. radiology and retinal image analyses). Health intelligence uses tools and methods from artificial intelligence and data science to provide better insights, reduce waste and wait time, and increase speed, service efficiencies, level of accuracy, and productivity in health care and medicine.
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