1,710 research outputs found

    I Wonder What\u27s the Matter With the Moon?

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    https://digitalcommons.library.umaine.edu/mmb-vp/4859/thumbnail.jp

    Indepth Analysis of Medical Dataset Mining: A Comparitive Analysis on a Diabetes Dataset Before and After Preprocessing

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    Most of the healthcare organizations and medical research institutions store their patient’s data digitally for future references and for planning their future treatments. This heterogeneous medical dataset is very difficult to analyze due to its complexity and volume of data, in addition to having missing values and noise which makes this mining a tedious task. Efficient classification of medical dataset is a major data mining problem then and now. Diagnosis, prediction of diseases and the precision of results can be improved if relationships and patterns from these complex medical datasets are extracted efficiently. This paper analyses some of the major classification algorithms such as C4.5 ( J48), SMO, Naïve Bayes, KNN Classification algorithms and Random Forest and the performance of these algorithms are compared using WEKA. Performance evaluation of these algorithms is based on Accuracy, Sensitivity and Specificity and Error rate. The medical data set used in this study are Heart-Statlog Medical Data Set which holds medical data related to heart disease and Pima Diabetes Dataset which holds data related to Diabetics. This study contributes in finding the most suitable algorithm for classifying medical data and also reveals the importance of preprocessing in improving the classification performance. Comparative study of various performances of machine learning algorithms is done through graphical representation of the results. Keywords: Data Mining, Health Care, Classification Algorithms, Accuracy, Sensitivity, Specificity, Error Rat

    The association between mentoring and training outcomes in junior doctors in medicine: an observational study.

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    OBJECTIVE: To determine quantitatively if a positive association exists between the mentoring of junior doctors and better training outcomes in postgraduate medical training within the UK. DESIGN: Observational study. PARTICIPANTS: 117 trainees from the East of England Deanery (non-mentored group) and the recently established Royal College of Physicians (RCP) Mentoring scheme (mentored group) who were core medical trainees (CMTs) between 2015 and 2017 completed an online survey. Trainees who received mentoring at the start of higher specialty training, incomplete responses and trainees who were a part of both the East of England deanery and RCP Mentoring scheme were excluded leaving 85 trainees in the non-mentored arm and 25 trainees in the mentored arm. Responses from a total of 110 trainees were analysed. MAIN OUTCOME MEASURES: Pass rates of the various components of the Membership of the Royal College of Physicians (MRCP) (UK) examination (MRCP Part 1, MRCP Part 2 Written and MRCP Part 2 PACES), pass rates at the Annual Review of Competency Progression (ARCP), trainee involvement in significant events, clinical incidents or complaints and trainee feedback on career progression and confidence. RESULTS: Mentored trainees reported higher pass rates of the MRCP Part 1 exam versus non-mentored trainees (84.0% vs 42.4%, p<0.01). Mentored international medical graduates (IMGs) reported higher pass rates than non-mentored IMGs in the MRCP Part 2 Written exam (71.4% vs 24.0%, p<0.05). ARCP pass rates in mentored trainees were observed to be higher than non-mentored trainees (95.8% vs 69.9%, p<0.05). Rates of involvement in significant events, clinical incidents and complaints in both groups did not show any statistical difference. Mentored trainees reported higher confidence and career progression. CONCLUSIONS: A positive association is observed between the mentoring of CMTs and better training outcomes. Further studies are needed to investigate the causative effects of mentoring in postgraduate medical training within the UK

    Passive acoustic tracking of the three-dimensional movements and acoustic behaviour of toothed whales in close proximity to static nets

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    Funding: Department for Environment, Food and Rural Affairs, UK Government (Grant Number(s): ME6052; Grant recipient(s): Jamie Macaulay, Allen Kingston, Simon Northridge, Alexander Coram). University of St Andrews.1. Entanglement in net fisheries (static and drift) is the largest known cause of direct anthropogenic mortality to many small cetacean species, including harbour porpoise (Phocoena phocoena), in UK waters. Despite this, little is known about the behaviour of small cetaceans in proximity to nets. 2. We have developed a passive acoustic monitoring (PAM) system for tracking the fine-scale three-dimensional (3D) movements of echolocating cetaceans around actively fishing nets by localising their acoustic clicks. The system consists of two compact four-channel acoustic recorders with sample-synchronised sensor packages that use 3D motion tracking technology to accurately calculate log orientation, depth, water temperature and ambient light level. Two recorders were used in tandem, with each one attached to and floating above the net floatline. The system can be deployed during normal fishing operations by a trained researcher or experienced fisheries observer. Recordings were analysed in PAMGuard software and the 3D positions of echolocating animals in the vicinity of the system were calculated using an acoustic particle filter-based localisation method. 3. We present findings from four deployments in UK waters (each 1–2 days in duration) in which 12 distinct harbour porpoise encounters yielded a sufficient number of detected clicks to track their movements around the net. The tracks show a variety of behaviours, including multiple instances of animals actively foraging in close proximity to the fishing net. 4. We show that a relatively inexpensive PAM system, which is practical to deploy from active fishing vessels, is capable of providing highly detailed data on harbour porpoise behaviour around nets. As harbour porpoises are the one of the most difficult species to localise, this methodology is likely to be suitable for elucidating the behaviour of many other toothed whale species in a variety of situations.Publisher PDFPeer reviewe

    Clinical predictors of all‐cause mortality in patients presenting to specialist heart failure clinic with raised NT‐proBNP and no heart failure

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    Aims Clinical outcomes for patients suspected of having heart failure (HF) who do not meet the diagnostic criteria of any type of HF by echocardiography remain unknown. The aim of this study was to investigate the clinical predictors of all‐cause mortality in patients with suspected HF, a raised N‐terminal pro‐b‐type natriuretic peptide (NTproBNP) and who do not meet the diagnostic criteria of any type of HF by echocardiography. Methods and results Relevant data were taken from the S heffield HEA rt F ailure (SHEAF) registry (222349P4). The inclusion criteria were presence of symptoms raising suspicion of HF, NTproBNP > 400 pg/mL, and preserved left ventricular function. Exclusion criteria were any type of HF by echocardiography. The outcome was defined as all‐cause mortality. Cox proportional‐hazards regression model was used to investigate the association between the survival time of patients and clinical variables; 1031 patients were identified with NTproBNP > 400 pg/mL but who did not have echocardiographic evidence of HF. All‐cause mortality was 21.5% (222 deaths) over the mean follow‐up (FU) period of 6 ± 2 years. NTproBNP was similar in patients who were alive or dead (P = 0.96). However, age (HR 1, P 627 pg/mL, NYHA class predicted death (II, 19.6%; III, 27.4%; IV, 66.7%; P < 0.01). Conclusions Patients with no HF on echocardiography but raised NTproBNP suffer excess mortality particularly in the presence of certain clinical variables. Age, male gender, worsening CKD stage, presence of COPD, and dementia are independently associated with all‐cause mortality in these patients. An NTproBNP > 627 pg/mL coupled with NYHA class could identify patients at greatest risk of death

    Cardiac MRI for the prognostication of heart failure with preserved ejection fraction: A systematic review and meta-analysis

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    Background Cardiac magnetic resonance imaging (MRI) is emerging as an important imaging tool in the assessment of heart failure with preserved ejection fraction (HFpEF). This systematic review and meta-analysis aim to synthesise and consolidate the current literature on cardiac MRI for prognostication of HFpEF. Methods design Systematic review and meta-analysis. Data sources: Scopus (PubMed and Embase) for studies published between 2008 and 2019. Eligibility criteria for study selection were studies that evaluated the prognostic role of cardiac MRI in HFpEF. Random effects meta-analyses of the reported hazard ratios (HR) for clinical outcomes was performed. Results Initial screening identified 97 studies. From these, only nine (9%) studies met all the criteria. The main cardiac MRI methods that demonstrated association to prognosis in HFpEF included late gadolinium enhancement (LGE) assessment of scar (n = 3), tissue characterisation with T1-mapping (n = 4), myocardial ischaemia (n = 1) and right ventricular dysfunction (RVSD) (n = 1). The pooled HR for all 9 studies was 1.52 (95% CI 1.05–1.99, P < 0.01). Sub-evaluation by cardiac MRI methods revealed varying HRs: LGE (net n = 402, HR = 1.6, 95% CI 0.42–2.78, P = 0.008); T1-mapping (n = 1623, HR = 1.25, 95% CI 0.891–1.60, P < 0.001); myocardial ischaemia or RVSD (n = 325, HR = 3.19, 95% CI 0.30–6.08, P = 0.03). Conclusion This meta-analysis demonstrates that multiparametric cardiac MRI has value in prognostication of patients with HFpEF. HFpEF patients with a detectable scar on LGE, fibrosis on T1-mapping, myocardial ischaemia or RVSD appear to have a worse prognosis. PROSPERO registration number CRD42020187228
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