On the relevance of the “genetics-based” approach to medicine for sociological perspectives on medical specialization

This paper draws on a study on the development of medical genetics as a medical specialism in the UK and Canada to reflect on how local and national contexts affect specialty formation. The paper begins by supporting earlier findings in the literature that stress, first, technological innovations as driving specialty formation, and, second, the domination of physicians in the division of medical labour. Beyond this, however, the paper explores the specific circumstances under which geneticists set about turning their work into a medical specialism based on a “genetics-based approach” to illness and how “medical genetics” as a specialism was assessed and configured to fit national and regional health service requirements

Exploring the Attitudes and Beliefs of Audiology Students About People Who Are Deaf or Hard of Hearing

This study was undertaken to explore and understand the attitudes and beliefs of audiology students about Deaf and Hard of Hearing people. The problem of practice was that some audiologists continue to advise parents not to sign with their Deaf or Hard of Hearing children. This problem was studied using the conceptual framework of General Systems Theory, looking at the problem through the lens of Critical Disability Theory, to determine if audiology students view Deaf and Hard of Hearing people from a medical model or from a social/cultural model. Using a qualitative case study methodology, I interviewed six first-year doctor of audiology (AuD) students at a university on the west coast of the United States to delve deeply into their attitudes and beliefs about Deaf and Hard of Hearing people. This study found that these audiology students had overall social/cultural attitudes about Deaf people on the Attitudes to Deafness Scale. Yet, in case-study interviews, which provided a more in-depth look at the views of the students, the terminology the students used demonstrated some institutionalized audist attitudes and beliefs. Every student showed a mixture of medical and social/cultural beliefs. The students made a distinction between the words “Deaf” and “Hard of Hearing.” All the students believed that parents of Deaf children should be offered “communication options” – (signed or spoken language). The four students who had studied American Sign Language (ASL) and Deaf culture were more open to the use of ASL. The two students who had the lowest scores on the Attitudes to Deafness Scale had no experience or background in ASL and demonstrated a preference for amplification technology and spoken language. The students believed that Hard of Hearing children should be raised with spoken language only. The students had a positive attitude about ASL but demonstrated a preference for spoken language. The audiology students understood their role in the medical system, but did not yet understand their part in the Deaf education system. They believed that parent-to-parent support is important but did not understand how audiologists might collaborate with the Deaf community and with teachers of the Deaf as families journey through the process of raising Deaf and Hard of Hearing children

Client applications and server-side docker for management of RNASeq and/or VariantSeq workflows and pipelines of the GPRO suite

The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called “RNASeq” and “VariantSeq” to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, “RNASeq” and “VariantSeq” are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Server-Side requires a Linux operating system, PHP, SQL, Python, bash scripting, and third-party software. The GPRO Server-Side can be installed, via a Docker container, in the user’s PC under any operating system or on remote servers, as a cloud solution. “RNASeq” and “VariantSeq” are both available as desktop (RCP compilation) and web (RAP compilation) applications. Each application has two execution modes: a step-by-step mode enables each step of the workflow to be executed independently, and a pipeline mode allows all steps to be run sequentially. “RNASeq” and “VariantSeq” also feature an experimental, online support system called GENIE that consists of a virtual (chatbot) assistant and a pipeline jobs panel coupled with an expert system. The chatbot can troubleshoot issues with the usage of each tool, the pipeline jobs panel provides information about the status of each computational job executed in the GPRO Server-Side, while the expert system provides the user with a potential recommendation to identify or fix failed analyses. Our solution is a ready-to-use topic specific platform that combines the user-friendliness, robustness, and security of desktop software, with the efficiency of cloud/web applications to manage pipelines and workflows based on command line interface software.This work was supported by the Marie Sklodowska-Curie OPATHY project grant agreement 642095, the pre-doctoral research fellowship from MINECO Industrial Doctorates (Grant 659 DI-17-09134); Grant TSI-100903-2019-11 from the Secretary of State for Digital Advancement from Ministry of Economic Affairs and Digital Transformation, Spain; the Expedient IDI-2021-158274-a from the Ministry of Science and Innovation, Spain; and the ThinkInAzul program supported by MCIN with funding from European Union NextGenerationEU (PRTR-C17.I1) and Generalitat Valenciana (THINKINAZUL/2021/024).Peer Reviewed"Article signat per 18 autors/es: Ahmed Ibrahem Hafez, Beatriz Soriano, Aya Allah Elsayed,Ricardo Futami,Raquel Ceprian, Ricardo Ramos-Ruiz, Genis Martinez, Francisco Jose Roig, Miguel Angel Torres-Font, Fernando Naya-Catala, Josep Alvar Calduch-Giner, Lucia Trilla-Fuertes, Angelo Gamez Pozo, Vicente Arnau, Jose Maria Sempere-Luna, Jaume Perez-Sanchez, Toni Gabaldon and Carlos Llorens "Postprint (published version

Client Applications and Server-Side Docker for Management of RNASeq and/or VariantSeq Workflows and Pipelines of the GPRO Suite

The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called 'RNASeq' and 'VariantSeq' to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, 'RNASeq' and 'VariantSeq' are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Server-Side requires a Linux operating system, PHP, SQL, Python, bash scripting, and third-party software. The GPRO Server-Side can be installed, via a Docker container, in the user's PC under any operating system or on remote servers, as a cloud solution. 'RNASeq' and 'VariantSeq' are both available as desktop (RCP compilation) and web (RAP compilation) applications. Each application has two execution modes: a step-by-step mode enables each step of the workflow to be executed independently, and a pipeline mode allows all steps to be run sequentially. 'RNASeq' and 'VariantSeq' also feature an experimental, online support system called GENIE that consists of a virtual (chatbot) assistant and a pipeline jobs panel coupled with an expert system. The chatbot can troubleshoot issues with the usage of each tool, the pipeline jobs panel provides information about the status of each computational job executed in the GPRO Server-Side, while the expert system provides the user with a potential recommendation to identify or fix failed analyses. Our solution is a ready-to-use topic specific platform that combines the user-friendliness, robustness, and security of desktop software, with the efficiency of cloud/web applications to manage pipelines and workflows based on command line interface software

A Machine Learning Approach for Prediction of Hospital Bed Availability

Las camas de internación constituyen un recurso escaso en las instituciones hospitalarias, los datos, en cambio, no. En el presente trabajo se argumenta que, haciendo uso de técnicas de aprendizaje automático, puede sacarse provecho del enorme volumen de data disponible en los sistemas de información de hospitales y sanatorios para construir soluciones de analytics que potencien la eficiente utilización de las camas de internación mediante la mejora del proceso de toma de decisiones. Con el objetivo de poner a prueba esta hipótesis, se trabajó en conjunto con una de las instituciones hospitalarias más importantes de la ciudad de Buenos Aires. El foco del trabajo estuvo puesto en la construcción de un modelo de aprendizaje automático que pudiera predecir la probabilidad de que un paciente sea dado de alta en las próximas veinticuatro horas, en función de su historia clínica, datos demográficos y algunos otros factorales ambientales. Para lograrlo se aplicaron técnicas de ingeniería de datos y aprendizaje supervisado, en el contexto de un problema de clasificación. Se experimentó con diferentes algoritmos así como formas de abordar la representación de atributos para sacar el máximo provecho de la data disponible. Como resultado, se obtuvo un modelo con un rendimiento prometedor que alcanza un puntaje de 0.84 de área bajo la curva ROC y ha demostrado generalizar muy bien en datos desconocidos. Dicho modelo fue la base sobre la cual se montó una herramienta de pronóstico de altas. Esta solución permite obtener tres predicciones, con diferentes niveles de incertidumbre asociada, de las altas esperadas en el Sanatorio para la fecha especificada. Los "niveles de confianza" reportados fueron obtenidos mediante un ejercicio de simulación sobre la data histórica que permitió comparar el pronóstico de la herramienta con el escenario observado en la realidad. El equipo de gestión de operaciones del hospital en cuestión ha hecho explícito su interés en la solución propuesta, ya que evalúan que el modelo tiene un enorme potencial para facilitar el proceso de planificación de camas y, de esta manera, ayudar a mejorar la eficiencia operacional del sanatorio.Hospital beds are a scarce resource for healthcare facilities, data is not. In this thesis, we argue that machine learning techniques could take advantage of the abundant amount of data available at hospitals information systems inorder to build analytics solutions that could propel the efficiet utilization of beds by improving the management decission making process. In order to test this hypothesis we have worked together with one of the most relevant medical institutions in Buenos Aires. The focus of our work has been placed in building a machine learning model that could predict the probability of a certain patient being discharged during the following twenty four hours, based on his medical records as well as his demographic data and some environmental factors. To this aim, data engineering and supervised learning techniques have been applied in the context of a classification task. We have experimented with different algorithms as well as feature representation approaches to make the most out of the data at hand. As a result, a model with a promising performance of 0.84 AUC-ROC score was obtained, and its results have demonstrated to generalize quite well on unseen data. This model was the base on top of which a discharges forecaster tool was developed. This solution is able to return three different predictions of the hospital discharges for a specified date with different "confidence levels" associated, thus providing management with a risk-informed prediction of hospital beds availaibility. The "confidence" reported for each of the forecasts was obtained using a simulation approach for historic data where we were able to contrast the forecast output with the actual scenario. The hospital management team has made explicit its interest in the solution, as they assess it has an enourmous potential for facilitating the bed planning process and by doing so improving the hospital operational efficiency

Prospectus, November 21, 1979

HAPPY THANKSGIVING; Campus Question: What does Thanksgiving mean to you?; Week in Review: Across the globe, In the nation, Throughout the state, Around town; Briefs: Help for finding money, CPR presented, Women to demo fair fighting, Income tax help tender, Drug uses and abuses explained by Dr. Rowan, \u27Salt of the Earth\u27 program feature, meet the Prezes Nov. 26 and 27, WPCD airs new show for women; History of Thanksgiving comes from many lands; Krannert events are varied; Letter to editor: Lonesome man wants pen pals; Faculty Focus: Register to vote, and vote in 1980!; Classifieds; Woodfield trip filled up; PC basketball team has its ups and downs; Gymnastics exhibition at PC December 1; VB to play now, organize later; Fast Freddy wins modestlyhttps://spark.parkland.edu/prospectus_1979/1003/thumbnail.jp

“Our objective wasn’t to belittle people’s behavior”: the history of gestational diabetes, 1921-1991

The emergence of the disease concept of Gestational Diabetes Mellitus during the late twentieth century was a product of collaborative efforts between physicians, medical researchers, businesses, and government agencies. This work is fundamentally an institutional history of medicine, situated in three specific genres within the field: disease creation studies, the examination of U.S. public health, and healthcare consumer history. This work traces changes in scientific and medical views, as well as the broader shift in how diseases are defined as that process moved out of the medical clinic and research lab into the halls of policy makers and government agencies. Scientific discovery and understanding emanated from the work of medical researchers, but the post-World War II era in the United States saw government agencies and healthcare businesses gain important roles in defining diseases and in creating consumer identities for patients. This was especially visible with gestational diabetes because many of the women who made up the rising numbers of new cases in the second half of the twentieth century came from lower-income groups who accessed their healthcare through government-subsidized programs like Medicaid. Through a range of historical sources, I examine the development of this dynamic relationship between medical knowledge and practice; business ideologies and approaches in an expanding healthcare market; and government policy on healthcare

Performance Evaluation of Hyperbolic Position Location Technique in Cellular Wireless Networks

This study addresses the wireless geolocation problem that has been an attractive subject for the last few years after Federal Communications Commission (FCC) mandate for wireless service providers to locate emergency 911 users with a high degree of accuracy -within a radius of 125 meters, 67 percent of the time by October 2001. There are a number of different geolocation technologies that have been proposed. These include, Assisted GPS (A-GPS), network-based technologies such as Enhanced Observed Time Difference (E-OTD), Time Difference of Arrival (TDOA), Angle of Arrival (AOA), and Cell of Origin (COO). This research focuses on network based techniques, namely the more prominent TDOA which is also called hyperbolic position location technique. The main problem in time-based positioning systems is solving nonlinear hyperbolic equations derived from set of TDOA estimates. Two algorithms are implemented as a solution to this problem: A closed form solution and a Least Squares (LS) algorithm. Accuracy and computational efficiency performances are compared in a wireless system established using DGPS measurements in Dayton, OH area