Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

The accessibility and acceptability of self-management support interventions for men with long term conditions: a systematic review and meta-synthesis of qualitative studies

Background: Self-management support interventions can improve health outcomes, but their impact is limited by the numbers of people able or willing to access them. Men’s attendance at existing self-management support services appears suboptimal despite their increased risk of developing many of the most serious long term conditions. The aim of this review was to determine whether current self-management support interventions are acceptable and accessible to men with long term conditions, and explore what may act as facilitators and barriers to access of interventions and support activities. Methods: A systematic search for qualitative research was undertaken on CINAHL, EMBASE, MEDLINE, PsycINFO and Social Science Citation Index, in July 2013. Reference lists of relevant articles were also examined. Studies that used a qualitative design to explore men’s experiences of, or perceptions towards, self-management support for one or more long term condition were included. Studies which focused on experiences of living with a long term condition without consideration of self-management support were excluded. Thirty-eight studies met the inclusion criteria. A meta-ethnography approach was employed to synthesise the findings. Results: Four constructs associated with men’s experience of, and perceptions towards, self management support were identified: 1) need for purpose; 2) trusted environments; 3) value of peers; and 4) becoming an expert. The synthesis showed that men may feel less comfortable participating in self-management support if it is viewed as incongruous with valued aspects of their identity, particularly when activities are perceived to challenge masculine ideals associated with independence, stoicism, and control. Men may find self-management support more attractive when it is perceived as action-oriented, having a clear purpose, and offering personally meaningful information and practical strategies that can be integrated into daily life. Conclusions: Self-management support is most likely to be successful in engaging men when it is congruent with key aspects of their masculine identity. In order to overcome barriers to access and fully engage with interventions, some men may need self-management support interventions to be delivered in an environment that offers a sense of shared understanding, connectedness, and normality, and involves and/or is facilitated by men with a shared illness experience

Seasonality of Plasmodium falciparum transmission: a systematic review

This article is fully open access and the published version is available free of charge from the jounal website.http://www.malariajournal.com/content/14/1/343Background Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has “strongly seasonal” transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized. Methods The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. Results and discussion 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). Discussion Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location. Conclusions The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales. Keywords: Plasmodium falciparum ; Seasonality; Climatic driversAcknowledgements This work was supported by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health. DLS is funded by a grant from the Bill & Melinda Gates Foundation (OPP1110495), which also supports RCR. PMA is grateful to the University of Utrecht for supporting him with The Belle van Zuylen Chair. PWG is a Career Development Fellow (K00669X) jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement and receives support from the Bill and Melinda Gates Foundation (OPP1068048, OPP1106023)

Effects of tropical cyclones on catchment sediment delivery to coastal ecosystems

Coastal areas in the tropics are remarkably vulnerable to extreme weather-related events (e.g. floods, storm surge, erosion), which are expected to intensify in the future. Erosion of catchments is affected by changes in climate and vegetation, which alters the production of sediment transported into coastal areas and can lead to the loss of important ecosystem services. In many areas in the tropics, cyclones and depressions (TCs) produce the largest floods and massive discharges of sediment, which can affect coastal habitats in wetlands, lagoons and reefs. Here we focus on the Pacific Islands, but the methodology can be used in any tropical catchment affected by cyclones. A hydro-sedimentological model was used to analyse the sediment outputs of the Dreketi River (Fiji) and their relationship with cyclone activity over the last 45 years. The model was developed based on satellite and ground information on topography, soils, land use, and climatic data. The sediment export was related to TCs in the area, which were identified using the Southwest Pacific Enhanced Archive of Tropical Cyclones (SPEArTC) database. TC-related precipitation events were found to be three times more intense than non-TC events, and the average annual contribution of TCs to sediment export was about 25 %, with years contributing more than 50 %. TC-related events produced six times the sediment export of non-TC events, indicating a strong relation with precipitation intensity. Relations between precipitation rate and sediment export were developed for both TC and non-TC events, which can be used to predict the effects of increase of cyclone activity in the future

The cystic fibrosis microbiome in an ecological perspective and its impact in antibiotic therapy

The recent focus on the cystic fibrosis (CF) complex microbiome has led to the recognition that the microbes can interact between them and with the host immune system, affecting the disease progression and treatment routes. Although the main focus remains on the interactions between traditional pathogens, growing evidence supports the contribution and the role of emergent species. Understanding the mechanisms and the biological effects involved in polymicrobial interactions may be the key to improve effective therapies and also to define new strategies for disease control. This review focuses on the interactions between microbe-microbe and host-microbe, from an ecological point of view, discussing their impact on CF disease progression. There are increasing indications that these interactions impact the success of antimicrobial therapy. Consequently, a new approach where therapy is personalized to patients by taking into account their individual CF microbiome is suggested.Portuguese Foundation for Science and Technology (FCT), the strategic funding of UID/BIO/04469/2013-CEB and UID/EQU/00511/2013-LEPABE units. This study was also supported by FCT and the European Community fund FEDER, through Program COMPETE, under the scope of the Projects “DNA mimics” PIC/IC/82815/2007, RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462), “BioHealth—Biotechnology and Bioengineering approaches to improve health quality”, Ref. NORTE-07-0124-FEDER-000027 and NORTE-07-0124-FEDER-000025—RL2_ Environment and Health, co-funded by the Programa Operacional Regional do Norte (ON.2 – O Novo Norte), QREN, FEDER. The authors also acknowledge the grant of Susana P. Lopes (SFRH/BPD/95616/2013) and of the COST-Action TD1004: Theragnostics for imaging and therapy

The 'law of requisite variety' may assist climate change negotiations:a review of the Kyoto and Durban meetings

Ashby wrote about cybernetics, during which discourse he described a Law that attempts to resolve difficulties arising in complex situations – he suggested using variety to combat complexity. In this paper, we note that the delegates to the UN Framework Convention on Climate Change (UNFCCC) meeting in Kyoto, 1997, were offered a ‘simplifying solution’ to cope with the complexity of discussing multiple pollutants allegedly contributing to ‘climate change’. We assert that the adoption of CO2eq has resulted in imprecise thinking regarding the ‘carbon footprint’ – that is, ‘CO2’ – to the exclusion of other pollutants. We propose, as Ashby might have done, that the CO2eq and other factors within the ‘climate change’ negotiations be disaggregated to allow careful and specific individual solutions to be agreed on each factor. We propose a new permanent and transparent ‘action group’ be in charge of agenda setting and to manage the messy annual meetings. This body would be responsible for achieving accords at these annual meetings, rather than forcing this task on national hosts. We acknowledge the task is daunting and we recommend moving on from Ashby's Law to Beer's Viable Systems approach

Genetic approaches to understanding the causes of stuttering

Stuttering is a common but poorly understood speech disorder. Evidence accumulated over the past several decades has indicated that genetic factors are involved, and genetic linkage studies have begun to identify specific chromosomal loci at which causative genes are likely to reside. A detailed investigation of one such region on chromosome 12 has identified mutations in the GNPTAB gene that are associated with stuttering in large families and in the general population. Subsequent studies identified mutations in the functionally related GNPTG and NAGPA genes. Mutations in these genes disrupt the lysosomal targeting pathway that generates the Mannose 6-phosphate signal, which directs a diverse group of enzymes to their target location in the lysosome of the cell. While mutations in these three genes can be identified in less than 10% of cases of familial stuttering, this knowledge allows a variety of new studies that can help identify the neuropathology that underlies this disorder

Improved Resolution Haplogroup G Phylogeny in the Y Chromosome, Revealed by a Set of Newly Characterized SNPs

Background: Y-SNP haplogroup G (hgG), defined by Y-SNP marker M201, is relatively uncommon in the United States general population, with only 8 additional sub-markers characterized. Many of the previously described eight sub-markers are either very rare (2–4%) or do not distinguish between major populations within this hg. In fact, prior to the current study, only 2 % of our reference Caucasian population belonged to hgG and all of these individuals were in sub-haplogroup G2a, defined by P15. Additional Y-SNPs are needed in order to differentiate between individuals within this haplogroup. Principal Findings: In this work we have investigated whether we could differentiate between a population of 63 hgG individuals using previously uncharacterized Y-SNPs. We have designed assays to test these individuals using all known hgG SNPs (n = 9) and an additional 16 unreported/undefined Y-SNPS. Using a combination of DNA sequence and genetic genealogy databases, we have uncovered a total of 15 new hgG SNPs that had been previously reported but not phylogenetically characterized. Ten of the new Y-SNPs are phylogenetically equivalent to M201, one is equivalent to P15 and, interestingly, four create new, separate haplogroups. Three of the latter are more common than many of the previously defined Y-SNPs. Y-STR data from these individuals show that DYS385*12 is present in (70%) of G2a3b1-U13 individuals while only 4 % of non-G2a3b1-U13 individuals posses the DYS385*12 allele. Conclusions: This study uncovered several previously undefined Y-SNPs by using data from several database sources. Th

Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed