For computers to serve humanity adequately they must be able to understand human speech and language. Only then will we have ...
The mind is this century's scientific frontier. Exploring it with intelligent use of technology will give us ...
The advent of “big data” — huge document collections and large datasets derived from government and commercial sources, including social media sites, mobile phones and transaction data — is offering new ways to understand and predict human behavior. Can this potential be exploited for the good of society? What social policy opportunities are presented by big data? What are the dangers?
Nowhere is the "big data" problem more technically challenging than with text. Words, sentences, paragraphs and documents contain information vital to commerce, science, and public governance. "Big data" has begun to tranform science, especially the genomic- and neuro-sciences. The insights afforded by the analysis of large volumes of textual data are yet to be fully understood and appreciated. The social sciences have yet to reap the rewards of "big data."
Computational neuroscience is poised to give us the most significant window ever into the human mind and human behavior. As with "big data" we must ask: How do we exploit this potential for social good? How do we guard against intrusive and unethical exploitations of the mind?
The data is out there. Now how do we use it to improve health?See "Health Datapalooza" for new ideas from companies, startups, academics, government agencies and individuals.
"Big Data" collected from responses to health questionsNational Cancer Institute's Health Information National Trends Survey
Business case development and strategic technology assessment in data science"Big data" opportunities associated with natural-language processing (NLP), text data mining, speech and language technologies, cognitive neuroscience technology, information extraction and synthesis Read More
Technology consulting and development• Speech and conversational interfaces • Home healthcare reporting • Healthcare robotics • Clinical information systems • Patient information systems • Consoumer health education • The electronic health record (EHR) • Text data mining -- scientific literature, clinical trials, genomic databases, consumer data • Integration of heterogeneous knowledge sources -- WordNet, UMLS, Gene Ontology • Construction and management of ontologies and controlled vocabularies • Machine learning techniques • Information retrieval methods and evaluation • Natural language processing (NLP) and its applications Read More