Epistemological Beliefs and Knowledge among Physicians: A Questionnaire Survey

Background: All sciences share a common underlying epistemological domain, which gives grounds to and characterizes their nature and actions. Insofar as physicians depend on scientific knowledge, it would be helpful to assess their knowledge regarding some theoretical foundations of science. Objectives: 1.To assess resident physicians' knowledge of concepts and principles underlying all sciences. 2. To determine, to what extent physicians' epistemological beliefs and attitudes are compatible with the scientific paradigm. Design: A questionnaire was administered to 161 resident physicians at three hospitals in Lima, Peru. Results: 237 resident physicians were selected, 161 (68%) of whom agreed to answer the survey. 67% of respondents indicated they did not know what epistemology is, 21% were able to correctly define epistemology; 24% of the residents knew the appropriate definition of scientific theory. No respondents knew the philosophical presumptions of science; and 48% took a relativistic stand towards knowledge. Conclusions: There appear to be deficiencies in the knowledge of scientific theoretical foundations among physicians

Vampires, Viruses and Verbalisation: Bram Stoker’s Dracula as a genealogical window into fin-de-siècle science

This paper considers Bram Stoker’s novel Dracula, published in 1897, as a window into techno-scientific and sociocultural developments of the fin-de-siècle era, ranging from blood transfusion and virology up to communication technology and brain research, but focusing on the birth of psychoanalysis in 1897, the year of publication. Stoker’s literary classic heralds a new style of scientific thinking, foreshadowing important aspects of post-1900 culture. Dracula reflects a number of scientific events which surfaced in the 1890s but evolved into major research areas that are still relevant today. Rather than seeing science and literature as separate realms, moreover, Stoker’s masterpiece encourages us to address the ways in which techno-scientific and psycho- cultural developments mutually challenge and mirror one another, so that we may use his novel to deepen our understanding of emerging research practices and vice versa (Zwart 2008, 2010). Psychoanalysis plays a double role in this. It is the research field whose genealogical constellation is being studied, but at the same time (Lacanian) psychoanalysis guides my reading strategy. Dracula, the infectious, undead Vampire has become an archetypal cinematic icon and has attracted the attention of numerous scholars (Browning & Picart 2009). The vampire complex built on various folkloristic and literary sources and culminated in two famous nineteenth-century literary publications: the story The Vampyre by John Polidori (published in 1819)2 and Stoker’s version. Most of the more than 200 vampire movies released since Nosferatu (1922) are based on the latter (Skal 1990; Browning & Picart 2009; Melton 2010; Silver & Ursini 2010). Yet, rather than on the archetypal cinematic image of the Vampire, I will focus on the various scientific ideas and instruments employed by Dracula’s antagonists to overcome the threat to civilisation he represents. Although the basic storyline is well-known, I will begin with a plot summary

Towards the implementation of a preference-and uncertain-aware solver using answer set programming

Logic programs with possibilistic ordered disjunction (or LPPODs) are a recently defined logic-programming framework based on logic programs with ordered disjunction and possibilistic logic. The framework inherits the properties of such formalisms and merging them, it supports a reasoning which is nonmonotonic, preference-and uncertain-aware. The LPPODs syntax allows to specify 1) preferences in a qualitative way, and 2) necessity values about the certainty of program clauses. As a result at semantic level, preferences and necessity values can be used to specify an order among program solutions. This class of program therefore fits well in the representation of decision problems where a best option has to be chosen taking into account both preferences and necessity measures about information. In this paper we study the computation and the complexity of the LPPODs semantics and we describe the algorithm for its implementation following on Answer Set Programming approach. We describe some decision scenarios where the solver can be used to choose the best solutions by checking whether an outcome is possibilistically preferred over another considering preferences and uncertainty at the same time.Postprint (published version

The Rhesus Factor and Disease Prevention

First published by the Wellcome Trust Centre for the History of Medicine at UCL, 2004. ©The Trustee of the Wellcome Trust, London, 2004. All volumes are freely available online at: www.history.qmul.ac.uk/research/modbiomed/wellcome_witnesses/Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Annotated and edited transcript of a Witness Seminar held on 3 June 2003. Introduction by Professor Doris T Zallen.Consists of the edited transcripts of Witness SeThe prevention of rhesus disease of the newborn is a stunning medical success story. This disease afflicted thousands of newborns each year, causing serious health problems, even death. Yet from the early 1940s to the 1970s – British and American researchers uncovered the basis of the disease and developed the medical intervention that could prevent its occurrence. Many of the key steps leading to this remarkable achievement took place at the University of Liverpool School of Medicine. Chaired by Professor Sir David Weatherall, this Witness Seminar examines the factors that triggered these studies and the challenges that confronted scientists and clinicians; the intellectual, institutional, and social factors that guided the work; the crucial insights; and the vistas that the prevention of rhesus disease has opened in fetal medicine. Participants include Professor Robin Coombs, the late Professor Ronald Finn, Dr Nevin Hughes-Jones, Professor Patrick Mollison, Dr Archie Norman, Dr Derrick Tovey, Professor Charles Whitfield, Professor John Woodrow and Professor Doris Zallen. Zallen, D T, Christie D A, Tansey E M. (eds) (2004) The Rhesus factor and disease prevention, Wellcome Witnesses to Twentieth Century Medicine, vol. 22. London: The Wellcome Trust Centre for the History of Medicine at UCL. ISBN 978 0 85484 099 1minars organized by the History of Twentieth Century Medicine Group and held at the Wellcome Institute for the History of Medicine.The Wellcome Trust Centre for the History of Medicine at University College London is funded by the Wellcome Trust,which is a registered charity, no. 210183

Traditional meditation, mindfulness and psychodynamic approach: An integrative perspective

The purpose of this article is to consolidate the inter-theoretical bridge between psychodynamic approach and TM, beyond the apparent incompatibility. Our impression is that even if some authors have already worked in order to fill the gap between TM and psychodynamic psychotherapy at theoretical level, this integration could be underrated and these efforts remain isolated. This could be due mainly to ambiguities in the translation of those terms with respect to the fundaments of core concepts of both perspectives, and a lack of empirical research on psychodynamic and meditation. Psychodynamic approach could embrace those aspects of TM that have been less developed in MBIs\u2019 theory and practice. Moreover, an integration of modern mindfulness practices into a psychodynamic framework should be explored. Further empirical studies and theoretical considerations are needed to corroborate testable hypotheses and comparing classical and combine

Combining expert knowledge and databases for risk management

Correctness, transparency and effectiveness are the principalattributes of knowledge derived from databases. In current data miningresearch there is a focus on efficiency improvement of algorithms forknowledge discovery. However important limitations of data mining canonly be dissolved by the integration of knowledge of experts in thefield, encoded in some accessible way, with knowledge derived formpatterns in the database. In this paper we will in particular discussmethods for combining expert knowledge and knowledge derived fromtransaction databases.The framework proposed is applicable to widevariety of risk management problems. We will illustrate the method ina case study on fraud discovery in an insurance company.risk management;datamining;knowledge discovery;knowledge based systems

Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?

After being collected for patient care, Observational Health Data (OHD) can further benefit patient well-being by sustaining the development of health informatics and medical research. Vast potential is unexploited because of the fiercely private nature of patient-related data and regulations to protect it. Generative Adversarial Networks (GANs) have recently emerged as a groundbreaking way to learn generative models that produce realistic synthetic data. They have revolutionized practices in multiple domains such as self-driving cars, fraud detection, digital twin simulations in industrial sectors, and medical imaging. The digital twin concept could readily apply to modelling and quantifying disease progression. In addition, GANs posses many capabilities relevant to common problems in healthcare: lack of data, class imbalance, rare diseases, and preserving privacy. Unlocking open access to privacy-preserving OHD could be transformative for scientific research. In the midst of COVID-19, the healthcare system is facing unprecedented challenges, many of which of are data related for the reasons stated above. Considering these facts, publications concerning GAN applied to OHD seemed to be severely lacking. To uncover the reasons for this slow adoption, we broadly reviewed the published literature on the subject. Our findings show that the properties of OHD were initially challenging for the existing GAN algorithms (unlike medical imaging, for which state-of-the-art model were directly transferable) and the evaluation synthetic data lacked clear metrics. We find more publications on the subject than expected, starting slowly in 2017, and since then at an increasing rate. The difficulties of OHD remain, and we discuss issues relating to evaluation, consistency, benchmarking, data modelling, and reproducibility.Comment: 31 pages (10 in previous version), not including references and glossary, 51 in total. Inclusion of a large number of recent publications and expansion of the discussion accordingl

Audio Cartography: Visual Encoding of Acoustic Parameters

Our sonic environment is the matter of subject in multiple domains which developed individual means of its description. As a result, it lacks an established visual language through which knowledge can be connected and insights shared. We provide a visual communication framework for the systematic and coherent documentation of sound in large-scale environments. This consists of visual encodings and mappings of acoustic parameters into distinct graphic variables that present plausible solutions for the visualization of sound. These candidate encodings are assembled into an application-independent, multifunctional, and extensible design guide. We apply the guidelines and show example maps that acts as a basis for the exploration of audio cartography

Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets

In this paper we review the application of logic synthesis methods for uncovering minimal structures in observational/medical datasets. Traditionally used in digital circuit design, logic synthesis has taken major strides in the past few decades and forms the foundation of some of the most powerful concepts in computer science and data mining. Here we provide a review of current state of research in application of logic synthesis methods for data analysis and provide a demonstrative example for systematic application and reasoning based on these methods