Digging for data that can change our world

AITopics Original Links

Scientific research is being added to at an alarming rate: the Human Genome Project alone is generating enough documentation to "sink battleships". So it's not surprising that academics seeking data to support a new hypothesis are getting swamped with information overload. As data banks build up worldwide, and access gets easier through technology, it has become easier to overlook vital facts and figures that could bring about groundbreaking discoveries. The government's response has been to set up the National Centre for Text Mining, the world's first centre devoted to developing tools that can systematically analyse multiple research papers, abstracts and other documents, and then swiftly determine what they contain. Text mining uses artificial intelligence techniques to look in texts for entities (a quality or characteristic, such as a date or job title) and concepts (the relationship between two genes, for example).


Knowledge Discovery in RNA Sequence Families of HIV Using Scalable Computers

AAAI Conferences

The prediction of RNA secondary structure on the basis of sequence information is an important tool in biosequence analysis. However, it has typically been restricted to molecules containing no more than 4000 nucleotides due to the computational complexity of the underlying dynamic programming algorithm used. We desribe here an approach to RNA sequence analysis based upon scalable computers, which enables molecules containing up to 20,000 nucleotides to be analysed.


How big data can change intensive care

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A team of data scientists, researchers and clinicians from UNSW Sydney have won a major prize at the second annual Healthcare Artificial Intelligence Datathon held at the National University of Singapore (NUS). The two-day event – organised jointly by the National University Health System (NUHS), Massachusetts Institute of Technology (MIT) and NUS – hosted more than 200 local and international data scientists and clinicians last weekend to address current problems in healthcare with the latest machine learning and artificial intelligence technologies. The joint UNSW-NUS team won first prize in the Critical Care Track, competing against eight other teams to analyse clinical data contained in the MIT/Philips eICU Collaborative Research Database, comprising information on more than 200,000 patients treated in intensive care units in US hospitals over the past five years. The UNSW-NUS team included researchers Oluwadamisola Sotade, Dr Mark Hanly and Oisin Fitzgerald from UNSW's Centre for Big Data Research in Health, Dr Tim Churches, data scientist from the Ingham Institute for Applied Medical Research and UNSW South Western Sydney Clinical School, and Dr Peter Straka from UNSW Mathematics and Statistics. "The installation of next-generation electronic medical records systems in ICUs and throughout hospitals enable very sophisticated machine-learning and artificial intelligence algorithms to be developed to assist busy clinicians in patient care and treatment decision making." said Dr Churches.


Big data, big wins in medicine

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An ambitious University of California initiative to create a central repository for clinical data from all six UC health systems is advancing medicine and transforming the process of medical discovery itself. Speaking at UC Health Data Day in San Diego, Atul Butte, M.D., Ph.D., chief data scientist, UC Health, described a new era in biomedical research, driven by the vast amounts of electronic medical record data. "Some are now saying the traditional scientific method of asking questions then making observations is becoming obsolete," Butte said. "We already have a data deluge." Across the UC medical centers, there are billions of data points related to patient care, stored within the UC Health Data Warehouse.


Big Data, Big Wins in Medicine at UC Health

#artificialintelligence

An ambitious University of California initiative to create a central repository for clinical data from all six UC health systems is advancing medicine and transforming the process of medical discovery itself. Speaking at UC Health Data Day in San Diego, Atul Butte, MD, PhD, chief data scientist, UC Health, described a new era in biomedical research, driven by the vast amounts of electronic medical record data. "Some are now saying the traditional scientific method of asking questions then making observations is becoming obsolete," Butte said. "We already have a data deluge." Across the UC medical centers, there are billions of data points related to patient care, stored within the UC Health Data Warehouse.