Time-Series Embedded Feature Selection Using Deep Learning: Data Mining Electronic Health Records for Novel Biomarkers

As health information technologies continue to advance, routine collection and digitisation of patient health records in the form of electronic health records present as an ideal opportunity for data-mining and exploratory analysis of biomarkers and risk factors indicative of a potentially diverse domain of patient outcomes. Patient records have continually become more widely available through various initiatives enabling open access whilst maintaining critical patient privacy. In spite of such progress, health records remain not widely adopted within the current clinical statistical analysis domain due to challenging issues derived from such “big data”.Deep learning based temporal modelling approaches present an ideal solution to health record challenges through automated self-optimisation of representation learning, able to man-ageably compose the high-dimensional domain of patient records into data representations able to model complex data associations. Such representations can serve to condense and reduce dimensionality to emphasise feature sparsity and importance through novel embedded feature selection approaches. Accordingly, application towards patient records enable complex mod-elling and analysis of the full domain of clinical features to select biomarkers of predictive relevance.Firstly, we propose a novel entropy regularised neural network ensemble able to highlight risk factors associated with hospitalisation risk of individuals with dementia. The application of which, was able to reduce a large domain of unique medical events to a small set of relevant risk factors able to maintain hospitalisation discrimination.Following on, we continue our work on ensemble architecture approaches with a novel cas-cading LSTM ensembles to predict severe sepsis onset within critical patients in an ICU critical care centre. We demonstrate state-of-the-art performance capabilities able to outperform that of current related literature.Finally, we propose a novel embedded feature selection application dubbed 1D convolu-tion feature selection using sparsity regularisation. Said methodology was evaluated on both domains of dementia and sepsis prediction objectives to highlight model capability and generalisability. We further report a selection of potential biomarkers for the aforementioned case study objectives highlighting clinical relevance and potential novelty value for future clinical analysis.Accordingly, we demonstrate the effective capability of embedded feature selection ap-proaches through the application of temporal based deep learning architectures in the discovery of effective biomarkers across a variety of challenging clinical applications

The Rate of Short-Duration Gamma-Ray Bursts in the Local Universe

Following the faint gamma-ray burst, GRB 170817A, coincident with a gravitational wave-detected binary neutron star merger at $d\sim40$ Mpc, we consider the constraints on a local population of faint short duration GRBs (defined here broadly as $T_{90}<4$ s). We review proposed low-redshift short-GRBs and consider statistical limits on a $d\lessapprox200$ Mpc population using Swift/Burst Alert Telescope (BAT), Fermi/Gamma-ray Burst Monitor (GBM), and Compton Gamma-Ray Observatory (CGRO) Burst and Transient Source Experiment (BATSE) GRBs. Swift/BAT short-GRBs give an upper limit for the all-sky rate of $<4$ y$^{-1}$ at $d<200$ Mpc, corresponding to $<5$% of SGRBs. Cross-correlation of selected CGRO/BATSE and Fermi/GBM GRBs with $d<100$ Mpc galaxy positions returns a weaker constraint of $\lessapprox12\ {\rm y^{-1}}$. A separate search for correlations due to SGR giant flares in nearby ($d<11$ Mpc) galaxies finds an upper limit of $<3\ {\rm y^{-1}}$. Our analysis suggests that GRB 170817A-like events are likely to be rare in existing SGRB catalogues. The best candidate for an analogue remains GRB 050906, where the Swift/BAT location was consistent with the galaxy IC0327 at $d\approx132$ Mpc. If binary neutron star merger rates are at the high end of current estimates, then our results imply that at most a few percent will be accompanied by detectable gamma-ray flashes in the forthcoming LIGO/Virgo science runs.Comment: 16 pages, 4 figures, 1 table. Published in Galaxies as part of the Special Issue, "Observations and Theory of Short GRBs at the Dawn of the Gravitational Wave Era

Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients Using Primary Care Electronic Health Records

A growing elderly population suffering from incurable, chronic conditions such as dementia present a continual strain on medical services due to mental impairment paired with high comorbidity resulting in increased hospitalization risk. The identification of at risk individuals allows for preventative measures to alleviate said strain. Electronic health records provide opportunity for big data analysis to address such applications. Such data however, provides a challenging problem space for traditional statistics and machine learning due to high dimensionality and sparse data elements. This article proposes a novel machine learning methodology: entropy regularization with ensemble deep neural networks (ECNN), which simultaneously provides high predictive performance of hospitalization of patients with dementia whilst enabling an interpretable heuristic analysis of the model architecture, able to identify individual features of importance within a large feature domain space. Experimental results on health records containing 54,647 features were able to identify 10 event indicators within a patient timeline: a collection of diagnostic events, medication prescriptions and procedural events, the highest ranked being essential hypertension. The resulting subset was still able to provide a highly competitive hospitalization prediction (Accuracy: 0.759) as compared to the full feature domain (Accuracy: 0.755) or traditional feature selection techniques (Accuracy: 0.737), a significant reduction in feature size. The discovery and heuristic evidence of correlation provide evidence for further clinical study of said medical events as potential novel indicators. There also remains great potential for adaption of ECNN within other medical big data domains as a data mining tool for novel risk factor identification

Synthesis, characterisation and performance of (TiO2)(0.18)(SiO2)(0.82) xerogel catalysts

The synthesis of high surface area xerogels has been achieved using the sol-gel route. Heptane washing was used during the stages of drying to minimise capillary pressures and hence preserve pore structure and maximise the surface area. SAXS data have identified that heptane washing during drying, in general, results in a preservation of the pore structure and surface areas of up to 450 m(2) g(-1). O-17 NMR showed that Ti is fully mixed into the silica network in all of the samples. XANES data confirm that reversible 4-fold Ti sites are more prevalent in samples with high surface areas, as expected. The calcined xerogels were tested for their catalytic activity using the epoxidation of cyclohexene with tert-butyl hydroperoxide (TBHP) as a test reaction, with excellent selectivities and reasonable percentage conversions. FT-IR spectroscopy has revealed that the catalytic activity is correlated with the intensity of the Si-O-Ti signal, after accounting for variations in Si-OH and Si-O-Si. The most effective catalyst was produced with heptane washing, a calcination temperature of 500 degreesC, and a heating rate of 5 degreesC min(-1)

The Impact of Different Classification Criteria Sets on the Estimated Prevalence and Associated Risk Factors of Diastolic Dysfunction in Rheumatoid Arthritis

This study compared the estimated prevalence and potential determinants of left ventricular (LV) diastolic dysfunction upon applying different classification criteria in rheumatoid arthritis (RA). LV diastolic function was assessed echocardiographically by pulsed Doppler (E/A), tissue Doppler (E/e′, lateral and septal e′), and left atrial volume index in 176 RA patients. Relationships of traditional cardiovascular risk factors and RA characteristics with LV diastolic function and dysfunction according to previous and current criteria were determined in multivariate regression models. Waist-hip ratio was associated with E/A (standardised β (SE) = -0.28±0.09, p=0.0002) and lateral e′ (standardised β (SE) = 0.26±0.09, p=0.01); low diastolic blood pressure was related to E/e′ (standardised β (SE) = -0.16±0.08, p=0.04). Diastolic dysfunction prevalence differed upon applying previous (59%) compared to current (22%) criteria (p<0.0001). One SD increase in waist-hip ratio was associated with diastolic dysfunction when applying current criteria (OR = 2.61 (95% CI = 1.51–4.52), p=0.0006), whereas one SD increase in diastolic blood pressure was inversely related to diastolic dysfunction upon using previous criteria (OR = 0.57 (95% CI = 0.40–0.81), p=0.002). In conclusion, application of current and previous diastolic dysfunction criteria markedly alters the prevalence and risk factors associated with diastolic dysfunction in RA

Supported by The South African Medical Research Council (grant MRC2008_DES) and National Research Foundation

ABSTRACT. Objective. Depending on physiological context, the adipokine chemerin can reduce or enhance cardiovascular risk. We investigated whether chemerin concentrations represent cardiovascular disease risk in rheumatoid arthritis (RA). Methods. We assessed ELISA-determined chemerin concentrations and those of 4 early endothelial activation molecules as well as angiopoietin 2, which mediates angiogenesis and thereby contributes to advanced atherosclerosis, the common carotid artery intima-media thickness (cIMT), and carotid artery plaque by ultrasound in 236 patients (114 black and 122 white) with RA. Relationships were identified in potential confounder and mediator-adjusted mixed regression models. . The β (SE) for the chemerin-intima-media thickness relations in patients with overweight or generalized obesity and abdominal obesity were larger than in those without these characteristics (p &lt; 0.0001 and = 0.04, respectively). Conclusion. Chemerin is associated with endothelial activation and atherosclerosis in RA. Adiposity influences the chemerin-atherosclerotic phenotype relations i

Severe Acute Respiratory Syndrome–associated Coronavirus Infection

Whether severe acute respiratory syndrome–associated coronavirus (SARS-CoV) infection can be asymptomatic is unclear. We examined the seroprevalence of SARS-CoV among 674 healthcare workers from a hospital in which a SARS outbreak had occurred. A total of 353 (52%) experienced mild self-limiting illnesses, and 321 (48%) were asymptomatic throughout the course of these observations. None of these healthcare workers had antibody to SARS CoV, indicating that subclinical or mild infection attributable to SARS CoV in adults is rare

RBP3-retinopathy - inherited high myopia and retinal dystrophy: Genetic Characterization, Natural History, and Deep Phenotyping

Objective: To examine the genetic and clinical features and the natural history of RBP3-associated retinopathy. // Design: Multi-center international, retrospective, case series. // Setting: Three tertiary referral centers. // Participants: Adults and children, with molecularly confirmed RBP3-associated retinopathy. // Main Outcomes and Measures: Multi-center, international, retrospective, consecutive observational study in three tertiary referral centers of adults and children, with molecularly confirmed RBP3-retinopathy. The genetic, clinical and retinal imaging findings, including optical coherence tomography (OCT) and fundus autofluorescence (FAF), were investigated both cross-sectionally and longitudinally. The results of International standard full-field and pattern electroretinography (ERG; PERG) were reviewed. // Results: We ascertained 12 patients (5 females), from 10 families, with four patients previously reported. Eight novel disease-causing RBP3 variants were identified. Ten patients were homozygous. The mean age (±SD, range) of the group was 21.4 years (±19.1, 2.9-60.5 years) at baseline evaluation. All 12 patients were highly myopic with a mean spherical equivalent of -16.0D (range; -7.0D to -33.0D). Visual acuity was not significantly different between eyes and no significant anisometropia was observed. Mean best corrected visual acuity (BCVA) was 0.48 LogMAR (range; 0.2-1.35, SD; ± 0.29 LogMAR) at baseline. Eleven patients had longitudinal BCVA assessment, with a mean BCVA of 0.46 LogMAR after a mean follow-up of 12.6 years. All patients were symptomatic with reduced VA and myopia by the age of 7 years. All patients had myopic fundi and features in keeping with high myopia on OCT, including choroidal thinning. The 4 youngest patients had no fundus pigmentary changes, with the rest presenting with a variable degree of mid-peripheral pigmentation and macular changes. FAF showed variable phenotypes, ranging from areas of increased signal to advanced atrophy in older patients. OCT showed cystoid macular edema at presentation in three patients, which persisted during follow-up in two patients and resolved to atrophy for the third patient. The ERGs were abnormal in 9 of 9 cases, revealing variable relative involvement of rod and cone photoreceptors with additional milder dysfunction post-phototransduction in some. All but one had PERG evidence of macular dysfunction, severe in most. // Conclusions: This study details the clinical and functional phenotype of RBP3-retinopathy in the largest cohort reported to date. RBP3-retinopathy is a disease characterized by early onset, slow progression over decades, and high myopia. The phenotypic spectrum and natural history as described herein has prognostic and counselling implications. RBP3-related disease should be considered in children with high myopia and retinal dystrophy