Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography

We propose new methods for the prediction of 5-year mortality in elderly individuals using chest computed tomography (CT). The methods consist of a classifier that performs this prediction using a set of features extracted from the CT image and segmentation maps of multiple anatomic structures. We explore two approaches: 1) a unified framework based on deep learning, where features and classifier are automatically learned in a single optimisation process; and 2) a multi-stage framework based on the design and selection/extraction of hand-crafted radiomics features, followed by the classifier learning process. Experimental results, based on a dataset of 48 annotated chest CTs, show that the deep learning model produces a mean 5-year mortality prediction accuracy of 68.5%, while radiomics produces a mean accuracy that varies between 56% to 66% (depending on the feature selection/extraction method and classifier). The successful development of the proposed models has the potential to make a profound impact in preventive and personalised healthcare.Comment: 9 page

Using single nucleotide polymorphisms as a means to understanding the pathophysiology of asthma

Asthma is the most common chronic childhood disease in the developed nations, and is a complex disease that has high social and economic costs. Studies of the genetic etiology of asthma offer a way of improving our understanding of its pathogenesis, with the goal of improving preventive strategies, diagnostic tools, and therapies. Considerable effort and expense have been expended in attempts to detect specific polymorphisms in genetic loci contributing to asthma susceptibility. Concomitantly, the technology for detecting single nucleotide polymorphisms (SNPs) has undergone rapid development, extensive catalogues of SNPs across the genome have been constructed, and SNPs have been increasingly used as a method of investigating the genetic etiology of complex human diseases. This paper reviews both current and potential future contributions of SNPs to our understanding of asthma pathophysiology

Reconceptualizing the Human Social Niche: How It Came to Exist and How It Is Changing

In this paper we present a reconceptualization of the social dimension of the human niche and the evolutionary process that brought it into existence. We agree with many other evolutionary approaches that a key aspect of the human niche is a social environment consisting primarily of cooperating and altruistic individuals, not a Hobbesian social environment of “war of all against all.” However, in contrast to the conception of this social environment as consisting of individuals who, in Boyd and Richerson’s words, “cooperate with large groups of unrelated individuals,” we propose that it is more accurately described as consisting of cooperating individuals who currently are often nonkin but who, until relatively recently in human existence, were primarily, and in many cases almost exclusively, kin. In contrast to the conception of this social environment coming into existence by way of a process of selection within and between groups, we propose that it is the result of selection operating on traditions originated by ancestors and transmitted to their descendants. We use our fieldwork in three areas of the world (New Guinea, Ecuador, and Canada) to illustrate this process and how current social environments can be roughly placed on a continuum from traditional to nontraditional

Genome-wide linkage and association mapping of disease genes with the GAW14 simulated datasets

We combined the results of whole-genome linkage and association analyses to determine which markers were most strongly associated with Kofendrerd Personality Disorder. Using replicate 1 from the Genetic Analysis Workshop 14 Aipotu, Karangar, Danacaa, and New York City simulated populations, we determined that several markers showed significant linkage and association with disease status. We used both SNP and microsatellite markers to determine patterns and chromosomal regions of markers. Three consistently associated markers were C01R0050, C03R0280, and C10R0882. Using generalized linear mixed models, we modelled the effect of the three predefined phenotypic categories on disease status and concluded that the phenotypes defining the "anxiety-related" category best predicted the outcome

JLIN: A java based linkage disequilibrium plotter

BACKGROUND: A great deal of effort and expense are being expended internationally in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Techniques such as Linkage Disequilibrium mapping are being increasingly used to examine and compare markers across increasingly large datasets. Visualisation techniques are becoming essential to analyse the ever-growing volume of data and results available with any given analysis. RESULTS: JLIN (Java LINkage disequilibrium plotter) is a software package designed for customisable, intuitive visualisation of Linkage Disequilibrium (LD) across all common computing platforms. Customisation allows the user to choose particular visualisations, statistical measures and measurement ranges. JLIN also allows the user to export images of the LD visualisation in several common document formats. CONCLUSION: JLIN allows the user to visually compare and contrast the results of a range of statistical measures on the input dataset(s). These measures include the commonly used D' and r(2 )statistics and empirical p-values. JLIN has a number of unique and novel features that improve on existing LD visualisation tools

Lack of reproducibility of linkage results in serially measured blood pressure data

BACKGROUND: Using the longitudinal Framingham Heart Study data on blood pressure, we analyzed the reproducibility of linkage measures from serial cross-sectional surveys of a defined population by performing genome-wide model-free linkage analyses to systolic blood pressure (SBP) and history of hypertension (HTN) measured at five separate time points. RESULTS: The heritability of SBP was relatively stable over time, ranging from 11.6 to 23.5% (coefficient of variation = 25.7%). However, the variability in linkage results was much greater. The average correlation in LOD scores at any pair of time points was 0.46 for HTN (NPL All LOD) and 0.17 for SBP (Variance Components LOD). No evidence of reproducible linkage results was found, with a mean κ of 0.02 for linkage to HTN and -0.03 for SBP linkage. At loci with potential evidence for linkage (LOD > 1.0 at one or more time points), the correlation was even lower. The coefficient of variation at loci with potential evidence of linkage was 126% for HTN and 135% for SBP. None of 15 chromosomal regions for HTN and only one of 28 regions for SBP with potential evidence for linkage had a LOD > 1.0 at more than two of the five time points. CONCLUSION: These data suggest that, although heritability estimates at different time points are relatively robust, the reproducibility of linkage results in serial cross-sectional samples of a geographically defined population at successive time points is poor. This may explain in part the difficulty encountered in replicating linkage studies of complex phenotypes