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2 nd 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%
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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