24,050 research outputs found

    Cardiovascular Attributable Risk and Risk Factors Evaluations as a Matter of Statistics and Data Mining Confluences

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    Cardiovascular diseases represent a severe threat for humanity, being the first cause of death and hospitalization in both genders. An impressive number of studies have been developed in order to identify a set of factors causing this kind of illness, but only few of them were able to pay significant resources in analyzing large population samples (tens of thousands) and for longer periods of time (decades). This paper’s objective is to continue the previous researches of the eProCord project and to validate with concrete data the theoretical model developed for the attributable risk (AR). It will consider the same risk factors for myocardial infarction identified by INTERHEART study and the same work hypothesis. We will also evaluate if a certain value of the AR is also confirmed by the invoked disease of the patient. Using statistical and data mining tools we will investigate the prediction potential of the chosen factors and the opportunity to extend them in order to capture any cardiovascular disease. The empirical tests rely for now on a sample of 236 patients.Cardiovascular Disease, Myocardial Infarction, Attributable Risk, Roc, Data Mining, Classification

    Vol. 22 no. 2 Semester 2 (2011)

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    https://researchonline.nd.edu.au/in_principio2010s/1003/thumbnail.jp

    An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders

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    The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The bio-sensors of the proposed system assist in getting the current and precise status of the concerned patients so that in case of an emergency, the needful medical assistance can be provided. The novelty lies in the hybrid framework and the adequate support of chatbots, granular computing, context entity search and semantic analysis. The practical implementation of this system is very challenging and costly. However, it appears to be more operative and economical solution for diabetes and cardio patients.Comment: 11 PAGE

    Deep Learning in Cardiology

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    The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

    The Role of Early-Life Conditions in the Cognitive Decline due to Adverse Events Later in Life

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    Cognitive functioning of elderly individuals may be affected by events such as the loss of a (grand)child or partner or the onset of a serious chronic condition, and by negative economic shocks such as job loss or the reduction of pension benefits. It is conceivable that the impact of such events is stronger if conditions early in life were adverse. In this paper we address this using a Dutch longitudinal database that follows elderly individuals for more than 15 years and contains information on demographics, socio-economic conditions, life events, health, and cognitive functioning. We exploit exogenous variation in early-life conditions as generated by the business cycle. We also examine to what extent the cumulative effect of consecutive shocks later in life exceeds the sum of the separate effects, and whether economic and health shocks later in life reinforce each other in their effect on cognitive functioning.cognitive functioning, business cycle, bereavement, developmental origins, retirement, health, long-run effects, dementia

    A method of assessing the quality of pharmaceutical market and industry reports as a source to study access to medicines

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    This repository item contains a single issue of the Health and Development Discussion Papers, an informal working paper series that began publishing in 2002 by the Boston University Center for Global Health and Development. It is intended to help the Center and individual authors to disseminate work that is being prepared for journal publication or that is not appropriate for journal publication but might still have value to readers.Market and industry reports can be useful in studying access to medicines from a pharmaceutical market perspective. However, many market and industry reports lack some or much of the information required to conduct analyses to study access to medicines and are often not transparent in their data sources and research methodologies. The instrument developed in this study, titled the Pharmaceutical Market and Industry Report Assessment Tool (PIRAT), assesses the quality of pharmaceutical market and industry reports, specifically focusing on the needs of public health researchers, and includes criteria describing the content and quality of the market reports. The assessment tool generates an unweighted score indicating the relative strengths and weaknesses of reports

    mHealth in China and the United States: How Mobile Technology is Transforming Healthcare in the World's Two Largest Economies

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    In this paper, we explore ways mobile technology can help with these difficulties. Specifically, we look at avenues through which mobile devices boost productivity, aid communications, and help providers improve affordability, access, and treatment. Using data drawn from China and the United States as well as global trends, we look at recent developments andemerging opportunities in mobile health, or mHealth. We argue that mobile technology assists patients, health providers, and policymakers in several different respects. It helps patients by giving them tools to monitor their health conditions and communicate those results to physicians. It enables health providers to connect with colleagues and offers alternative sources of information for patients. It is also an important tool to inform policymakers on health delivery and medical outcomes

    Heart Failure Monitoring System Based on Wearable and Information Technologies

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    In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilitie

    Looking Ahead: Workforce Supply/Demand Analysis for New Jersey's Pharmaceutical and Medical Technology Industries

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    This analysis presents the results of a workforce supply and demand analysis of the pharmaceutical and medical technology industries in New Jersey
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