83 research outputs found
Modelling User Behaviour in Market Attribution: finding novel data features using machine learning
This paper presents an exploration of market attribution methods and the integration of user behaviour. Attribution is the measurement of interaction between marketing touchpoints and channels along the customer journey, improving customer insights and driving smarter business decisions. Improving the accuracy of attribution requires a deeper understanding of user behaviour, not just marketing channel credit assignment. Evidence has been provided regarding the problems in the standardized approach to behavioural modelling and alternatives have been presented. The study explores data provided by a British based jewellery company with an investigation into pre-existing data features that can aid with the analysis of user behaviour. The study contains over 10 million rows collected over 2 years and presents the initial findings made in the first 15 months of a PhD study
What do patients and the public know about clinical practice guidelines and what do they want from them? A qualitative study
Background Guideline producers are increasingly producing versions of guidelines for the public. The aim of this study was to explore what patients and the public understand about the purpose and production of clinical guidelines, and what they want from clinical guidelines to support their healthcare decisions. Methods Participants were purposively selected to represent a range of the likely users of patient versions of guidelines, including individuals with health conditions (diabetes and depression), general members of the public, health communication professionals and a group of young people. Participants were asked about their awareness and understanding of clinical guidelines and presented with scenario recommendations, or draft materials from patient guidelines to prompt discussion. Each discussion was facilitated by one or two researchers. All focus groups were recorded and transcribed prior to analysis. Data were analysed using framework analysis. Results We ran nine focus groups involving 62 individuals, supplemented by four interviews with people experiencing homelessness. Eight groups were held in Scotland, one in England. The four interviews were held in Scotland. The framework analysis yielded five themes: access and awareness; what patients want to know; properties of guidelines; presenting evidence; and format. Awareness of guidelines was low. Participants emphasised the need for information that enables them to choose between treatment options, including harms. They would like help with this from healthcare professionals, especially general practitioners. Participants differed in their support for the inclusion of numerical information and graphs. Conclusions Members of the public want information to help them choose between treatments, including information on harm, particularly to support shared decisions with health professionals. Presenting numerical information is a challenge and layered approaches that present information in stages may be helpful. Ignoring the themes identified in this study is likely to lead to materials that fail to support public and patient healthcare decisions
Impacts of temporal CO2 and climate trends on the detection of ocean anthropogenic CO2 accumulation
Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 25 (2011): GB3023, doi:10.1029/2010GB004009.A common approach for estimating the oceanic uptake of anthropogenic carbon dioxide (Canthro) depends on the linear approximation of oceanic dissolved inorganic carbon (DIC) from a suite of physical and biological ocean parameters. The extended multiple linear regression (eMLR) method assumes that baseline correlations and the resulting residual fields will remain constant with time even under the influence of secular climate changes. The validity of these assumptions over the 21st century is tested using a coupled carbon-climate model. Findings demonstrate that the influence of both changing climate and changing chemistry beyond 2–4 decades invalidates the assumption that the residual fields will remain constant resulting in significant errors in the eMLR estimate of Canthro. This study determines that the eMLR method is unable to describe Canthro uptake for a sampling interval of greater than 30 years if the error is to remain below 20% for many regions in the Southern Ocean, Atlantic Ocean, and western Pacific Ocean. These results suggest that, for many regions of the ocean basins, hydrographic field investigations have to be repeated at approximately decadal timescales in order to accurately predict the uptake of Canthro by the ocean if the eMLR method is used.This
work was supported by NOAA grant NA07OAR4310098 (SCD and RW)
and funding from the University of Hong Kong (NFG)
Pitfalls of predicting complex traits from SNPs
The success of genome-wide association studies (GWASs) has led to increasing interest in making predictions of complex trait phenotypes, including disease, from genotype data. Rigorous assessment of the value of predictors is crucial before implementation. Here we discuss some of the limitations and pitfalls of prediction analysis and show how naive implementations can lead to severe bias and misinterpretation of results
The Atacama Cosmology Telescope: A Measurement of the DR6 CMB Lensing Power Spectrum and its Implications for Structure Growth
We present new measurements of cosmic microwave background (CMB) lensing over
sq. deg. of the sky. These lensing measurements are derived from the
Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) CMB dataset, which
consists of five seasons of ACT CMB temperature and polarization observations.
We determine the amplitude of the CMB lensing power spectrum at
precision ( significance) using a novel pipeline that minimizes
sensitivity to foregrounds and to noise properties. To ensure our results are
robust, we analyze an extensive set of null tests, consistency tests, and
systematic error estimates and employ a blinded analysis framework. The
baseline spectrum is well fit by a lensing amplitude of
relative to the Planck 2018 CMB power spectra
best-fit CDM model and relative to
the best-fit model. From our lensing power
spectrum measurement, we derive constraints on the parameter combination
of
from ACT DR6 CMB lensing alone and
when combining ACT DR6 and Planck NPIPE
CMB lensing power spectra. These results are in excellent agreement with
CDM model constraints from Planck or
CMB power spectrum measurements. Our lensing measurements from redshifts
-- are thus fully consistent with CDM structure growth
predictions based on CMB anisotropies probing primarily . We find no
evidence for a suppression of the amplitude of cosmic structure at low
redshiftsComment: 45+21 pages, 50 figures. Prepared for submission to ApJ. Also see
companion papers Madhavacheril et al and MacCrann et a
The Atacama Cosmology Telescope: High-resolution component-separated maps across one-third of the sky
Observations of the millimeter sky contain valuable information on a number
of signals, including the blackbody cosmic microwave background (CMB), Galactic
emissions, and the Compton- distortion due to the thermal Sunyaev-Zel'dovich
(tSZ) effect. Extracting new insight into cosmological and astrophysical
questions often requires combining multi-wavelength observations to spectrally
isolate one component. In this work, we present a new arcminute-resolution
Compton- map, which traces out the line-of-sight-integrated electron
pressure, as well as maps of the CMB in intensity and E-mode polarization,
across a third of the sky (around 13,000 sq.~deg.). We produce these through a
joint analysis of data from the Atacama Cosmology Telescope (ACT) Data Release
4 and 6 at frequencies of roughly 93, 148, and 225 GHz, together with data from
the \textit{Planck} satellite at frequencies between 30 GHz and 545 GHz. We
present detailed verification of an internal linear combination pipeline
implemented in a needlet frame that allows us to efficiently suppress Galactic
contamination and account for spatial variations in the ACT instrument noise.
These maps provide a significant advance, in noise levels and resolution, over
the existing \textit{Planck} component-separated maps and will enable a host of
science goals including studies of cluster and galaxy astrophysics, inferences
of the cosmic velocity field, primordial non-Gaussianity searches, and
gravitational lensing reconstruction of the CMB.Comment: The Compton-y map and associated products will be made publicly
available upon publication of the paper. The CMB T and E mode maps will be
made available when the DR6 maps are made publi
The Atacama Cosmology Telescope: DR6 Gravitational Lensing Map and Cosmological Parameters
We present cosmological constraints from a gravitational lensing mass map
covering 9400 sq. deg. reconstructed from CMB measurements made by the Atacama
Cosmology Telescope (ACT) from 2017 to 2021. In combination with BAO
measurements (from SDSS and 6dF), we obtain the amplitude of matter
fluctuations at 1.8% precision,
and the Hubble
constant at
1.6% precision. A joint constraint with CMB lensing measured by the Planck
satellite yields even more precise values: ,
and . These measurements agree
well with CDM-model extrapolations from the CMB anisotropies measured
by Planck. To compare these constraints to those from the KiDS, DES, and HSC
galaxy surveys, we revisit those data sets with a uniform set of assumptions,
and find from all three surveys are lower than that from ACT+Planck
lensing by varying levels ranging from 1.7-2.1. These results motivate
further measurements and comparison, not just between the CMB anisotropies and
galaxy lensing, but also between CMB lensing probing on
mostly-linear scales and galaxy lensing at on smaller scales. We
combine our CMB lensing measurements with CMB anisotropies to constrain
extensions of CDM, limiting the sum of the neutrino masses to eV (95% c.l.), for example. Our results provide independent
confirmation that the universe is spatially flat, conforms with general
relativity, and is described remarkably well by the CDM model, while
paving a promising path for neutrino physics with gravitational lensing from
upcoming ground-based CMB surveys.Comment: 30 pages, 16 figures, prepared for submission to ApJ. Cosmological
likelihood data is here:
https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html ; likelihood
software is here: https://github.com/ACTCollaboration/act_dr6_lenslike . Also
see companion papers Qu et al and MacCrann et al. Mass maps will be released
when papers are publishe
GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe
Analysis of shared heritability in common disorders of the brain
ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders
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