On the Role of Entanglement in Schroedinger's Cat Paradox

In this paper we re-investigate the core of Schroedinger's 'cat paradox'. We argue that one has to distinguish clearly between superpositions of macroscopic cat states and superpositions of entangled states which comprise both the state of the cat. It is shown, that in the first instance recurrence to decoherence or other mechanisms is not necessary in this special case in order to explain the absence of macroscopic superpositions. Additionally, we present modified versions of two quantum optical experiments as experimenta crucis. Applied rigorously, quantum mechanical formalism reduces the problem to a mere pseudo-paradox.Comment: 10 pages; LaTeX; contact information update

Semantic validation of standard based electronic health record documents with W3C XML Schema

++43 1 40400 6693 (Phone) [email protected] 2 Summary Objectives. The goal of this article is to examine whether W3C XML Schema provides a practicable solution for the semantic validation of standard based electronic health record (EHR) documents. With semantic validation we mean that the EHR documents are checked for conformance with the underlying archetypes and reference model. Methods. We describe an approach that allows XML Schemas to be derived from archetypes based on a specific naming convention. The archetype constraints are augmented with additional components of the reference model within the XML Schema representation. A copy of the EHR document that is transformed according to the before-mentioned naming convention is used for the actual validation against the XML Schema. Results. We tested our approach by semantically validating EHR documents conformant to three different ISO/EN 13606 archetypes respective to three sections of the CDA implementation guide "Continuity of Care Document (CCD)" and an implementation guide for diabetes therapy data. We further developed a tool to automate the different steps of our semantic validation approach. Conclusions. For two particular kinds of archetype prescriptions, individual transformations are required for the corresponding EHR documents. Otherwise, a fully generic validation is possible. In general, we consider W3C XML Schema as a practicable solution for the semantic validation of standard based EHR documents

Improving the informational continuity of care in diabetes mellitus treatment with a nationwide Shared EHR system: Estimates from Austrian claims data

Purpose Shared Electronic Health Record (EHR) systems, which provide a health information exchange (HIE) within a community of care, were found to be a key enabler of informational continuity of diabetes mellitus (DM) care. Quantitative analyses of the actual contribution of Shared EHR systems to informational continuity of care are rare. The goal of this study was to quantitatively analyze (i) the degree of fragmentation of DM care in Austria as an indicator for the need for HIE, and (ii) the quantity of information (i.e. number of documents) from Austrian DM patients that would be made available by a nationwide Shared EHR system for HIE. Methods Our analyses are based on social security claims data of 7.9 million Austrians from 2006 and 2007. DM patients were identified through medication data and inpatient diagnoses. The degree of fragmentation was determined by the number of different healthcare providers per patient. The amount of information that would be made available by a nationwide Shared EHR system was estimated by the number of documents that would have been available to a healthcare provider if he had access to information on the patient’s visits to any of the other healthcare providers. As a reference value we determined the number of locally available documents that would have originated from the patient’s visits to the healthcare provider himself. We performed our analysis for two types of systems: (i) a “comprehensive” Shared EHR system (SEHRS), where each visit of a patient results in a single document (progress note), and (ii) the Austrian ELGA system, which allows four specific document types to be shared. Results 391,630 DM patients were identified, corresponding to 4.7% of the Austrian population. More than 90% of the patients received health services from more than one healthcare provider in one year. Both, the SEHRS as well as ELGA would have multiplied the available information during a patient visit in comparison to an isolated local EHR system; the median ratio of external to local medical documents was between 1:1 for a typical visit at a primary care provider (SEHRS as well as ELGA) and 39:1 (SEHRS) respectively 28:1 (ELGA) for a typical visit at a hospital. Conclusions Due to the high degree of care fragmentation, there is an obvious need for HIE for Austrian DM patients. Both, the SEHRS as well as ELGA could provide a substantial contribution to informational continuity of care in Austrian DM treatment. Hospitals and specialists would have gained the most amount of external information, primary care providers and pharmacies would have at least doubled their available information. Despite being the most important potential feeders of a national Shared EHR system according to our analysis, primary care providers will not tap their full corresponding potential under the current implementation scenario of ELGA

Evaluating web-based static, animated and interactive maps for injury prevention

This is the final version of the article. Available from PAGEpress via the DOI in this record.Public health planning can benefit from visual exploration and analysis of geospatial data. Maps and geovisualization tools must be developed with the user-group in mind. User-needs assessment and usability testing are crucial elements in the iterative process of map design and implementation. This study presents the results of a usability test of static, animated and interactive maps of injury rates and socio-demographic determinants of injury by a sample of potential end-users in Toronto, Canada. The results of the user-testing suggest that different map types are useful for different purposes and for satisfying the varying skill level of the individual user. The static maps were deemed to be easy to use and versatile, while the animated maps could be made more useful if animation controls were provided. The split-screen concept of the interactive maps was highlighted as particularly effective for map comparison. Overall, interactive maps were identified as the preferred map type for comparing patterns of injury and related socio-demographic risk factors. Information collected from the user-tests is being used to expand and refine the injury web maps for Toronto, and could inform other public health-related geo-visualization projects.Partial funding for this project was provided by the Natural Sciences and Engineering Research Council of Canada and the Canadian Institutes of Health Research

Swath-ms: a new data independent acquisition LC-MS methodology for quantitative complete proteome analysis

Comunicaciones a congreso

Integrating Decision-Making Support in Geocollaboration Tools

info:eu-repo/semantics/publishedVersio

Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge

Previous studies of artificial intelligence (AI) applied to dermatology have shown AI to have higher diagnostic classification accuracy than expert dermatologists; however, these studies did not adequately assess clinically realistic scenarios, such as how AI systems behave when presented with images of disease categories that are not included in the training dataset or images drawn from statistical distributions with significant shifts from training distributions. We aimed to simulate these real-world scenarios and evaluate the effects of image source institution, diagnoses outside of the training set, and other image artifacts on classification accuracy, with the goal of informing clinicians and regulatory agencies about safety and real-world accuracy.We designed a large dermoscopic image classification challenge to quantify the performance of machine learning algorithms for the task of skin cancer classification from dermoscopic images, and how this performance is affected by shifts in statistical distributions of data, disease categories not represented in training datasets, and imaging or lesion artifacts. Factors that might be beneficial to performance, such as clinical metadata and external training data collected by challenge participants, were also evaluated. 25?331 training images collected from two datasets (in Vienna [HAM10000] and Barcelona [BCN20000]) between Jan 1, 2000, and Dec 31, 2018, across eight skin diseases, were provided to challenge participants to design appropriate algorithms. The trained algorithms were then tested for balanced accuracy against the HAM10000 and BCN20000 test datasets and data from countries not included in the training dataset (Turkey, New Zealand, Sweden, and Argentina). Test datasets contained images of all diagnostic categories available in training plus other diagnoses not included in training data (not trained category). We compared the performance of the algorithms against that of 18 dermatologists in a simulated setting that reflected intended clinical use.64 teams submitted 129 state-of-the-art algorithm predictions on a test set of 8238 images. The best performing algorithm achieved 58·8% balanced accuracy on the BCN20000 data, which was designed to better reflect realistic clinical scenarios, compared with 82·0% balanced accuracy on HAM10000, which was used in a previously published benchmark. Shifted statistical distributions and disease categories not included in training data contributed to decreases in accuracy. Image artifacts, including hair, pen markings, ulceration, and imaging source institution, decreased accuracy in a complex manner that varied based on the underlying diagnosis. When comparing algorithms to expert dermatologists (2460 ratings on 1269 images), algorithms performed better than experts in most categories, except for actinic keratoses (similar accuracy on average) and images from categories not included in training data (26% correct for experts vs 6% correct for algorithms, p<0·0001). For the top 25 submitted algorithms, 47·1% of the images from categories not included in training data were misclassified as malignant diagnoses, which would lead to a substantial number of unnecessary biopsies if current state-of-the-art AI technologies were clinically deployed.We have identified specific deficiencies and safety issues in AI diagnostic systems for skin cancer that should be addressed in future diagnostic evaluation protocols to improve safety and reliability in clinical practice.Melanoma Research Alliance and La Marató de TV3.Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved

SOPHIE velocimetry of Kepler transit candidates XII. KOI-1257 b: a highly eccentric three-month period transiting exoplanet

In this paper we report a new transiting warm giant planet: KOI-1257 b. It was first detected in photometry as a planet-candidate by the ${\it Kepler}$ space telescope and then validated thanks to a radial velocity follow-up with the SOPHIE spectrograph. It orbits its host star with a period of 86.647661 d $\pm$ 3 s and a high eccentricity of 0.772 $\pm$ 0.045. The planet transits the main star of a metal-rich, relatively old binary system with stars of mass of 0.99 $\pm$ 0.05 Msun and 0.70 $\pm$ 0.07 Msun for the primary and secondary, respectively. This binary system is constrained thanks to a self-consistent modelling of the ${\it Kepler}$ transit light curve, the SOPHIE radial velocities, line bisector and full-width half maximum (FWHM) variations, and the spectral energy distribution. However, future observations are needed to confirm it. The PASTIS fully-Bayesian software was used to validate the nature of the planet and to determine which star of the binary system is the transit host. By accounting for the dilution from the binary both in photometry and in radial velocity, we find that the planet has a mass of 1.45 $\pm$ 0.35 Mjup, and a radius of 0.94 $\pm$ 0.12 Rjup, and thus a bulk density of 2.1 $\pm$ 1.2 g.cm$^{-3}$. The planet has an equilibrium temperature of 511 $\pm$ 50 K, making it one of the few known members of the warm-jupiter population. The HARPS-N spectrograph was also used to observe a transit of KOI-1257 b, simultaneously with a joint amateur and professional photometric follow-up, with the aim of constraining the orbital obliquity of the planet. However, the Rossiter-McLaughlin effect was not clearly detected, resulting in poor constraints on the orbital obliquity of the planet.Comment: 39 pages, 17 figures, accepted for publication in Astronomy & Astrophysic