5,045 research outputs found

    Designing a Predictive Coding System for Electronic Discovery

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    Not long ago, the concept of using predictive coding and other technologies to assist with the electronic discovery process seemed revolutionary. Da Silva Moore and Global Aerospace stand as the first major cases where judges strongly supported predictive coding.1-2 A recent Indiana case recognized it as a useful method for reducing the amount of potentially relevant evidence that has to be searched and culled.3 Within just a few short years, using predictive coding as part of an electronic discovery process is now considered acceptable and perhaps even expected. It is not difficult to appreciate the advantages of predictive coding and its superiority over a manual process at various steps of electronic discovery, particularly during the review step.4-11 However, questions still remain about the efficacy of the predictive coding process and the tools that are available.12-13 Because the use of predictive coding systems in law is still in its infancy, it presents us with an opportunity to design something that will not only take advantage of the power of big data and computational algorithms, but that will also incorporate design and usability principles to provide an attractive and easy-to-use interface for lawyers to interact with. Predictive coding uses natural language processing and other mathematical models to enhance search results, but the essence of these systems is that they actually learn and the precision of the retrieval improves as additional collections of evidence are entered. Behind-the-scenes will be a repository where all of the evidence for a case resides. Our system will assist the lawyers in reducing the time and cost of an electronic discovery process as well as minimize the chances for mistakes in determining which evidence is relevant to a case and which evidence can be withheld under attorney-client privilege, as attorney work-product or another confidentiality doctrine. 1. Da Silva Moore v. Publicis Groupe & MSL Group, No. 11 Civ. 1279, 2012 WL 607412 (ALC) (AJP) (S.D.N.Y. Feb. 24, 2012). 2. Global Aerospace, Inc. v. Landow Aviation, L.P., No. CL 61040 (Vir. Cir. Ct. Apr. 23, 2012). 3. In re Biomet, 2013 WL 1729682 (N.D. Ind. Apr. 18, 2013). 4. Alison Silverstein and Geoffrey Vance. E-Discovery Myth Busters: Why Predictive Coding is Safe, Successful and Smart. Peer to Peer, Vol. 29, No. 4, December 2013, pp. 66-69. 5. John Papageorge. Predictive Coding Gaining Support in Courts. Indiana Lawyer, January 29-February 11, 2014, p. 8. 6. Adam M. Acosta. Predictive Coding: The Beginning of a New E-Discovery Era. Res Gestae, October 2012, pp. 8-14. 7. Ajith (AJ) Samuel. Analytics Driving the E-Discovery Process. Peer to Peer, Vol. 28, No. 2, June 2012. 8. Richard Acello. Beyond Prediction: Technology-Assisted Review Enters the Lexicon. ABA Journal, August 2012, pp. 37, 70. 9. Barry Murphy. The Rise of Technology-Assisted Review (TAR). Peer to Peer, Vol. 28, No. 2, June 2012, pp. 10. Brian Ingram. Controlling E-Discovery Costs in a Big Data World. Peer to Peer, Vol. 29, No. 1, March 2013. 11. Hal Marcus and Susan Stone. Beyond Predictive Coding - The True Power of Data Analytics [webinar]. International Legal Technology Association, May 19, 2015. 12. Jessica Watts and Gareth Evans. Predictive Coding in the Real World [webinar]. International Legal Technology Association, August 5, 2015. 13. Danielle Bethea. Predictive Coding: Revolutionizing Review or Still Gaining Momentum? Litigation and Practice Support: ITLA White Paper, International Legal Technology Association, June 2014

    Health-state utilities in a prisoner population : a cross-sectional survey

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    Background: Health-state utilities for prisoners have not been described. Methods: We used data from a 1996 cross-sectional survey of Australian prisoners (n = 734). Respondent-level SF-36 data was transformed into utility scores by both the SF-6D and Nichol's method. Socio-demographic and clinical predictors of SF-6D utility were assessed in univariate analyses and a multivariate general linear model. Results: The overall mean SF-6D utility was 0.725 (SD 0.119). When subdivided by various medical conditions, prisoner SF-6D utilities ranged from 0.620 for angina to 0.764 for those with none/mild depressive symptoms. Utilities derived by the Nichol's method were higher than SF-6D scores, often by more than 0.1. In multivariate analysis, significant independent predictors of worse utility included female gender, increasing age, increasing number of comorbidities and more severe depressive symptoms. Conclusion: The utilities presented may prove useful for future economic and decision models evaluating prison-based health programs

    Toward unsupervised outbreak detection through visual perception of new patterns

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    <p>Abstract</p> <p>Background</p> <p>Statistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available.</p> <p>This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases.</p> <p>Methods</p> <p>The method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2<sup>nd </sup>version (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest.</p> <p>Results</p> <p>The method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED).</p> <p>Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data.</p> <p>Conclusion</p> <p>Using human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected.</p

    Conventional Radiology for Postmortem Imaging

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    This book offers a comprehensive overview of the forensic and radiological aspects of pathological findings, focusing on the most relevant medico-legal issues, such as virtual autopsy (virtopsy), anthropometric identification, post-mortem decomposition features and the latest radiological applications used in forensic investigations. Forensic medicine and radiology are becoming increasingly relevant in the international medical and legal field as they offer essential techniques for determining cause of death and for anthropometric identification. This is highly topical in light of public safety and economic concerns arising as a result of mass migration and international tensions. The book discusses the latest technologies applied in the forensic field, in particular computed tomography and magnetic resonance, which are continuously being updated. Radiological techniques are fundamental in rapidly providing a full description of the damage inflicted to add to witness and medical testimonies, and forensic/radiological anthropology supplies valuable evidence in cases of violence and abuse. Written by international experts, it is of interest to students and residents in forensic medicine and radiology. It also presents a new approach to forensic investigation for lawyers and police special corps as well as law enforcement agencies

    Between-airport heterogeneity in air toxics emissions associated with individual cancer risk thresholds and population risks

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    Abstract Background Airports represent a complex source type of increasing importance contributing to air toxics risks. Comprehensive atmospheric dispersion models are beyond the scope of many applications, so it would be valuable to rapidly but accurately characterize the risk-relevant exposure implications of emissions at an airport. Methods In this study, we apply a high resolution atmospheric dispersion model (AERMOD) to 32 airports across the United States, focusing on benzene, 1,3-butadiene, and benzo [a]pyrene. We estimate the emission rates required at these airports to exceed a 10-6 lifetime cancer risk for the maximally exposed individual (emission thresholds) and estimate the total population risk at these emission rates. Results The emission thresholds vary by two orders of magnitude across airports, with variability predicted by proximity of populations to the airport and mixing height (R2 = 0.74–0.75 across pollutants). At these emission thresholds, the population risk within 50 km of the airport varies by two orders of magnitude across airports, driven by substantial heterogeneity in total population exposure per unit emissions that is related to population density and uncorrelated with emission thresholds. Conclusion Our findings indicate that site characteristics can be used to accurately predict maximum individual risk and total population risk at a given level of emissions, but that optimizing on one endpoint will be non-optimal for the other.</p

    Spin-Rotation Symmetry Breaking in the Superconducting State of CuxBi2Se3

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    Spontaneous symmetry breaking is an important concept for understanding physics ranging from the elementary particles to states of matter. For example, the superconducting state breaks global gauge symmetry, and unconventional superconductors can break additional symmetries. In particular, spin rotational symmetry is expected to be broken in spin-triplet superconductors. However, experimental evidence for such symmetry breaking has not been conclusively obtained so far in any candidate compounds. Here, by 77Se nuclear magnetic resonance measurements, we show that spin rotation symmetry is spontaneously broken in the hexagonal plane of the electron-doped topological insulator Cu0.3Bi2Se3 below the superconducting transition temperature Tc=3.4 K. Our results not only establish spin-triplet superconductivity in this compound, but may also serve to lay a foundation for the research of topological superconductivity
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