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dhtobey Tobey

AutoMap: Project | CASOS - 0 views

www.casos.cs.cmu.edu/...automap

text-mining software semantic index Carnegie-Mellon

shared by dhtobey Tobey on 26 Apr 10 - Cached
  • AutoMap is a text mining tool that enables the extraction of network data from texts. AutoMap can extract content analytic data (words and frequencies), semantic networks, and meta-networks from unstructured texts developed by CASOS at Carnegie Mellon.  Pre-processors for handling pdf’s and other text formats exist.  Post-processors for linking to gazateers and belief inference also exist. The main functions of AutoMap are to extract, analyze, and compare texts in terms of concepts, themes, sentiment, semantic networks and the meta-networks extracted from the texts. AutoMap exports data in DyNetML and can be used interoperably with *ORA. AutoMap uses parts of speech tagging and proximity analysis to do computer-assisted Network Text Analysis (NTA). NTA encodes the links among words in a text and constructs a network of the linked words. AutoMap subsumes classical Content Analysis by analyzing the existence, frequencies, and covariance of terms and themes. AutoMap has been implemented in Java 1.5.0_07. It can operate in both a front end with gui, and backend mode. Main functionalities of AutoMap are: Extract, analyze and compare mental models of individuals and groups. Reveal structure of social and organizational systems from texts. AutoMap also offers a variety of techniques for pre-processing Natural Language: Named-Entity Recognition Stemming (Porter, KStem) Collocation (Bigram) Detection Extraction routines for dates, events, parts of speech Deletion Thesaurus development and application Flexible ontology usage Parts of Speech Tagging
  • dhtobey Tobey on 26 Apr 10
     
    Could this tool be useful for the knowledge exchange to develop automatic tagging and taxonomy creation?
dhtobey Tobey

Evidence-based medicine - Wikipedia, the free encyclopedia - 1 views

en.wikipedia.org/...Evidence-based_medicine

evidence-based-medicine community-desktop

shared by dhtobey Tobey on 30 Apr 10 - Cached
  • The systematic review of published research studies is a major method used for evaluating particular treatments. The Cochrane Collaboration is one of the best-known, respected examples of systematic reviews. Like other collections of systematic reviews, it requires authors to provide a detailed and repeatable plan of their literature search and evaluations of the evidence. Once all the best evidence is assessed, treatment is categoried as "likely to be beneficial", "likely to be harmful", or "evidence did not support either benefit or harm".
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      We need to find access to the Cochrane Collaboration -- this is obviously a large, extant community socializing the vetting of clinical evidence.  We should find out more about their methodology and supporting technology, if any.
  • Evidence-based medicine categorizes different types of clinical evidence and ranks them according to the strength of their freedom from the various biases that beset medical research. For example, the strongest evidence for therapeutic interventions is provided by systematic review of randomized, double-blind, placebo-controlled trials involving a homogeneous patient population and medical condition. In contrast, patient testimonials, case reports, and even expert opinion have little value as proof because of the placebo effect, the biases inherent in observation and reporting of cases, difficulties in ascertaining who is an expert, and more.
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      Is this ranking an emergent process supported by some type of knowledge exchange platform? What about consensus/dissensus analysis? Seems ripe for groupthink and manipulation or paradigm traps.
  • ...5 more annotations...
  • This process can be very human-centered, as in a journal club, or highly technical, using computer programs and information techniques such as data mining.
  • Level III: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      Need for LivingSurvey, LivingPapers, and LivingAnalysis.
  • Despite the differences between systems, the purposes are the same: to guide users of clinical research information about which studies are likely to be most valid. However, the individual studies still require careful critical appraisal.
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      In other words, there are wide differences of opinion (dissensus) that must be managed and used to inform decision-making.
  • The U.S. Preventive Services Task Force uses:[9] Level A: Good scientific evidence suggests that the benefits of the clinical service substantially outweighs the potential risks. Clinicians should discuss the service with eligible patients. Level B: At least fair scientific evidence suggests that the benefits of the clinical service outweighs the potential risks. Clinicians should discuss the service with eligible patients. Level C: At least fair scientific evidence suggests that there are benefits provided by the clinical service, but the balance between benefits and risks are too close for making general recommendations. Clinicians need not offer it unless there are individual considerations. Level D: At least fair scientific evidence suggests that the risks of the clinical service outweighs potential benefits. Clinicians should not routinely offer the service to asymptomatic patients. Level I: Scientific evidence is lacking, of poor quality, or conflicting, such that the risk versus benefit balance cannot be assessed. Clinicians should help patients understand the uncertainty surrounding the clinical service.
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      Relates well to Scott's idea of common problem being one of risk management.
  • AUC-ROC The area under the receiver operating characteristic curve (AUC-ROC) reflects the relationship between sensitivity and specificity for a given test. High-quality tests will have an AUC-ROC approaching 1, and high-quality publications about clinical tests will provide information about the AUC-ROC. Cutoff values for positive and negative tests can influence specificity and sensitivity, but they do not affect AUC-ROC.
    • dhtobey Tobey
      dhtobey Tobey on 30 Apr 10
       
      ROC curves are similar to PPT, though addressing a different and less impactful issue of system sensitivity and specificity, rather than reliability (consistency) as determined by PPT.
dhtobey Tobey

Open Innovation | Innovation Management - 0 views

www.innocentive.com

knowledge-exchange science ideas community research partner

shared by dhtobey Tobey on 25 Apr 10 - Cached
  • dhtobey Tobey on 25 Apr 10
     
    We believe in the power of open innovation, bringing together creative minds to create breakthrough solutions that touch every human life.Founded in 2001, InnoCentive connects companies, academic institutions, public sector and non-profit organizations, all hungry for breakthrough innovation, with a global network of more than 200,000 of the world's brightest minds on the world's first 1Open Innovation Marketplace™.These creative thinkers -- engineers, scientists, inventors, and business people with expertise in life sciences, engineering, chemistry, math, computer science, and entrepreneurship -- join the InnoCentive Solver™ community to solve some of the world's toughest challenges.Seeker™ organizations post their challenges on the InnoCentive web site, and offer registered Solvers significant financial awards for the best solutions. Seeker™ and Solver™ identities are kept completely confidential and secure, and InnoCentive manages the entire IP process.
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