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Explore the latest innovations in health informatics at the 2nd ACM SIGHIT International Health Informatics Symposium in Miami, Florida. Join experts from 38 countries presenting 269 papers on topics like data analytics, healthcare communication networks, and the role of Semantic Web. Engage with keynote speakers Professor Sophia Ananiadou and Jonathan R. Wolpaw on cutting-edge advancements in biomedical text mining and brain-computer interfaces. Attend tutorials on RDF, SPARQL, and interactive demos showcasing patient matching algorithms and social networking for disseminating information on stigmatized illnesses.
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2nd ACM SIGHIT International Health Informatics Symposium January 28-30, 2012 Miami, Florida, USA
Highlights • 223 attendees • 2 invited talks • Authors from 38 countries submitted 269 papers across the different tracks • 4 Panels, 3 Tutorials • Regular 10-page papers: 68 accepted - 25% • Short 5-page papers: 31 accepted • Demos: 8 accepted
Invited talks • Biomedical Text Mining for Semantic Search and Knowledge Discovery • Professor Sophia AnaniadouSchool of Computer ScienceUniversityofManchester • Brain-Computer Interfaces: Progress, Problems, and Possibilities • Jonathan R. Wolpaw, M.D.Chief, Laboratory of Neural Injury and Repair Universityof New York
Topics • Data • Data acquisition - Intelligentmedicaldevices and sensors • Data analytics, data mining, and machine learning • Knowledge management - Semantic Web, linkeddata • (Privacy) • Healthcare communication networks and environments • Interactions with health information technologies
Role of Semantic Web in Health Informatics • Tutorial • Introduction, RDF, SPARQL, … • Live Demo • Provides interface for medical staff to build they own queries instead of asking computer analytics . • Matching of patients based on similarity of one measurement/condition and finding correlation in others
DisseminatingInformationonStigmatizedIllnessesviaSocialNetworkingSitesDisseminatingInformationonStigmatizedIllnessesviaSocialNetworkingSites • Users to send anonymous messages (Veiled messages) to known friends. Recipients know that a message is from a friend of theirs, but not which friend • Trusted source + anonymity
Presentations • A Meta-analysis of ICT Adoption and Use by Medical Professionals in Sub-Saharan Africa • Human Motion Primitive Identification and Activity Recognition Using a Bag-of-Features Approach • Public Health Community Mining in YouTube