Mining and analysis of audiology data to find significant factors associated with tinnitus masker

Objectives: The objective of this research is to find the factors associated with tinnitus masker from the literature, and by using the large amount of audiology data available from a large NHS (National Health Services, UK) hearing aid clinic. The factors evaluated were hearing impairment, age, gender, hearing aid type, mould and clinical comments. Design: The research includes literature survey for factors associated with tinnitus masker, and performs the analysis of audiology data using statistical and data mining techniques. Setting: This research uses a large audiology data but it also faced the problem of limited data for tinnitus. Participants: It uses 1,316 records for tinnitus and other diagnoses, and 10,437 records of clinical comments from a hearing aid clinic. Primary and secondary outcome measures: The research is looking for variables associated with tinnitus masker, and in future, these variables can be combined into a single model to develop a decision support system to predict about tinnitus masker for a patient. Results: The results demonstrated that tinnitus maskers are more likely to be fit to individuals with milder forms of hearing loss, and the factors age, gender, type of hearing aid and mould were all found significantly associated with tinnitus masker. In particular, those patients having Age<=55 years were more likely to wear a tinnitus masker, as well as those with milder forms of hearing loss. ITE (in the ear) hearing aids were also found associated with tinnitus masker. A feedback on the results of association of mould with tinnitus masker from a professional audiologist of a large NHS (National Health Services, UK) was also taken to better understand them. The results were obtained with different accuracy for different techniques. For example, the chi-squared test results were obtained with 95% accuracy, for Support and Confidence only those results were retained which had more than 1% Support and 80% Confidence. Conclusions: The variables audiograms, age, gender, hearing aid type and mould were found associated with the choice of tinnitus masker in the literature and by using statistical and data mining techniques. The further work in this research would lead to the development of a decision support system for tinnitus masker with an explanation that how that decision was obtained

Publications on Chronic Disease in Coal Dependent Communities in Central Appalachia

CONTEXT: Agency and nonprofit reports have traditionally been the source of health information in Appalachia. Recently, publications have appeared in the literature associating coal mining, specifically mountain top mining, with numerous chronic health conditions spurring debate among environmental and industry interest groups. Publication quantity and quality were objectively assessed. This article reports on a literature review and analysis of publications on chronic disease in coal dependent communities in Appalachia. OBJECTIVE: To conduct a review and analysis of original, peer reviewed research publications on chronic health conditions in communities dependent on coal mining with a focus on central Appalachia and report on publication and research quantity and quality. DATA SOURCES: Thorough searches were conducted using PubMed, EBSCO, and CiNAHL computerized databases to identify original, peer-reviewed research articles addressing ‘Appalachia’, ‘health’ and ‘coal’. STUDY SELECTION: The computerized database search identified original research publications relevant to chronic health conditions (heart disease, lung disease, kidney disease, cancers, diabetes, obesity, etc.) and coal mining in central Appalachia. DATA EXTRACTION: Quantitative measures of the literature review provided information on author collaborations, year of publication, frequency of publication by contributing authors, etc. Journal impact factors were noted and other objective qualitative criteria were considered. DATA SYNTHESIS: Over 60 publications relevant to mining with 38 publications specific to Appalachia and health were identified. The publications were reviewed relative to relevance and article quality i.e., current, original research, application to central Appalachia and discussions of chronic human health and coal mining. Over the past five years most of the publications relevant to chronic disease and coal mining in central Appalachia resulted from a research group with a single common author. CONCLUSIONS: Science based evidence is needed and data must be provided by independent researchers from various disciplines of study to share different perspectives on how to alleviate the longstanding health disparities in central Appalachia. Studies will require the application of sound methodologies to validate the findings and support future interventions

Analytics and complexity: learning and leading for the future

There is growing interest in the application of learning analytics to manage, inform and improve learning and teaching within higher education. In particular, learning analytics is seen as enabling data-driven decision making as universities are seeking to respond a range of significant challenges that are reshaping the higher education landscape. Experience over four years with a project exploring the use of learning analytics to improve learning and teaching at a particular university has, however, revealed a much more complex reality that potentially limits the value of some analytics-based strategies. This paper uses this experience with over 80,000 students across three learning management systems, combined with literature from complex adaptive systems and learning analytics to identify the source and nature of these limitations along with a suggested path forward

The ethics of uncertainty for data subjects

Modern health data practices come with many practical uncertainties. In this paper, I argue that data subjects’ trust in the institutions and organizations that control their data, and their ability to know their own moral obligations in relation to their data, are undermined by significant uncertainties regarding the what, how, and who of mass data collection and analysis. I conclude by considering how proposals for managing situations of high uncertainty might be applied to this problem. These emphasize increasing organizational flexibility, knowledge, and capacity, and reducing hazard

A (digital) finger on the pulse

Complex Event Processing (CEP) is a computer-based technique used to track, analyse and process data in real-time (as an event happens). It establishes correlations between streams of information and matches to defined behaviour