Machine learning techniques for the prediction of indoor gamma-ray dose rates - Strengths, weaknesses and implications for epidemiology.

We investigate methods that improve the estimation of indoor gamma ray dose rates at locations where measurements had not been made. These new predictions use a greater range of modelling techniques and larger variety of explanatory variables than our previous examinations of this subject. Specifically, we now employ three types of machine learning models in addition to the geostatistical, nearest neighbour and other earlier models.

Spatial variation in housing construction material in low- and middle-income countries: A Bayesian spatial prediction model of a key infectious diseases risk factor and social determinant of health.

Housing infrastructure and quality is a major determinant of infectious disease risk and other health outcomes in regions where vector borne, waterborne and neglected tropical diseases are endemic. It is important to quantify the geographical distribution of improvements to dwelling components to identify and target resources towards populations at risk. This study aimed to model the sub-national spatial variation in housing materials using covariates with quasi-global coverage and use the resulting estimates to map predicted coverage across the world's low- and middle-income countries.

Precipitation Drives Frugivory in a Subtropical Generalist Herbivore, the Gopher Tortoise, and Alters Its Functional Role as a Seed Disperser.

Consumers employ a variety of foraging strategies, and oftentimes the foraging strategy employed is related to resource availability. As consumers acquire resources, they may interact with their resource base in mutualistic or antagonistic ways-falling along a mutualism-antagonism continuum-with implications for ecological processes such as seed dispersal. However, patterns of resource use vary temporally, and textbook herbivores may switch foraging tactics to become more frugivorous in periods of greater fleshy fruit availability.

Association of the Area Deprivation Index With Dementia Basic Workup and Diagnosis in Central and Western Virginia: A Cross-Sectional Study.

Background And Objectives: The Area Deprivation Index (ADI) provides a validated and multidimensional metric of areal disadvantage. Our goals were to determine if the ADI influences the likelihood of receiving workup based on published guidelines and an etiologic diagnosis of dementia in Central and Western Virginia.

Methods: We collected deidentified data from the electronic health record of individuals aged 50-105 years diagnosed with dementia at the University of Virginia (UVA) Medical Center (2016-2021) and at Carillion Clinic (2018-2021).

Comparison of Deep Learning Approaches for Conversion of International Classification of Diseases Codes to the Abbreviated Injury Scale.

The injury severity classifications generated from the Abbreviated Injury Scale (AIS) provide information that allows for standardized comparisons in the field of trauma injury research. However, the majority of injuries are coded in International Classification of Diseases (ICD) and lack this severity information. A system to predict injury severity classifications from ICD codes would be beneficial as manually coding in AIS can be time-intensive or even impossible for some retrospective cases.

Solar ultraviolet radiation exposure, and incidence of childhood acute lymphocytic leukaemia and non-Hodgkin lymphoma in a US population-based dataset.

Background: Acute lymphocytic leukaemia (ALL) and non-Hodgkin lymphoma (NHL) are among the commonest types of childhood cancer. Some previous studies suggested that elevated ultraviolet radiation (UVR) exposures increase ALL risk; many more indicate NHL risk is reduced.

Methods: We assessed age<20 ALL/NHL incidence in Surveillance, Epidemiology and End Results data using AVGLO-derived UVR irradiance/cumulative radiant exposure measures, using quasi-likelihood models accounting for underdispersion, adjusted for age, sex, racial/ethnic group and other county-level socioeconomic variables.

Pathophysiological Responses to Bloodstream Infection in Critically Ill Transplant Recipients Compared With Non-Transplant Recipients.

Background: Identification of bloodstream infection (BSI) in transplant recipients may be difficult due to immunosuppression. Accordingly, we aimed to compare responses to BSI in critically ill transplant and non-transplant recipients and to modify systemic inflammatory response syndrome (SIRS) criteria for transplant recipients.

Methods: We analyzed univariate risks and developed multivariable models of BSI with 27 clinical variables from adult intensive care unit (ICU) patients at the University of Virginia (UVA) and at the University of Pittsburgh (Pitt).

Smoothing Lexis diagrams using kernel functions: A contemporary approach.

Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc.

Evaluation of Neural Machine translation for conversion of International Classification of disease codes to the Abbreviated injury Scale.

The Abbreviated Injury Scale (AIS) is an essential tool for injury research since it allows for comparisons of injury severity among patients, however, the International Classification of Diseases (ICD) is more widely used to capture medical information. The problem of conversion between these two medical coding systems has similarities to the challenges encountered in language translation. We therefore hypothesize that neural machine translation (NMT), a deep learning technique which is commonly used for human language translation, could be used to convert ICD codes to AIS.

Perioperative systemic blood pressure parameters and clinical outcomes following 27g vitrectomy for diabetic tractional detachment repair.

Background: Extremes in perioperative blood pressures are known risk factors for adverse outcomes after surgical interventions. There is scarce literature studying these parameters as predictors of outcomes after ocular surgery.

Methods: This was a retrospective single-centre interventional cohort analysis to evaluate the relationship between perioperative (preoperative and intraoperative) blood pressure value and variability and postoperative visual and anatomic outcomes.

Neighborhood Deprivation and Association With Neonatal Intensive Care Unit Mortality and Morbidity for Extremely Premature Infants.

Importance: Socioeconomic status affects pregnancy and neurodevelopment, but its association with hospital outcomes among premature infants is unknown. The Area Deprivation Index (ADI) is a validated measure of neighborhood disadvantage that uses US Census Bureau data on income, educational level, employment, and housing quality.

Objective: To determine whether ADI is associated with neonatal intensive care unit (NICU) mortality and morbidity in extremely premature infants.

The Planetary Child Health & Enterics Observatory (Plan-EO): a protocol for an interdisciplinary research initiative and web-based dashboard for mapping enteric infectious diseases and their risk factors and interventions in LMICs.

Background: Diarrhea remains a leading cause of childhood illness throughout the world that is increasing due to climate change and is caused by various species of ecologically sensitive pathogens. The emerging Planetary Health movement emphasizes the interdependence of human health with natural systems, and much of its focus has been on infectious diseases and their interactions with environmental and human processes. Meanwhile, the era of big data has engendered a public appetite for interactive web-based dashboards for infectious diseases.

Race, Class, and Place Modify Mortality Rates for the Leading Causes of Death in the United States, 1999-2021.

Background: Race and ethnicity, socioeconomic class, and geographic location are well-known social determinants of health in the US. Studies of population mortality often consider two, but not all three of these risk factors.

Objectives: To disarticulate the associations of race (whiteness), class (socioeconomic status), and place (county) with risk of cause-specific death in the US.

Ordinal models to analyze strategy sophistication: Evidence from a learning trajectory efficacy study.

Investigators often rely on the proportion of correct responses in an assessment when describing the impact of early mathematics interventions on child outcomes. Here, we propose a shift in focus to the relative sophistication of problem-solving strategies and offer methodological guidance to researchers interested in working with strategies. We leverage data from a randomized teaching experiment with a kindergarten sample whose details are outlined in Clements et al.

Impact of race on heart rate characteristics monitoring in very low birth weight infants.

Background: A multicenter RCT showed that displaying a heart rate characteristics index (HRCi) predicting late-onset sepsis reduced mortality for VLBW infants. We aimed to assess whether HRCi display had a differential impact for Black versus White infants.

Methods: We performed secondary data analysis of Black and White infants enrolled in the HeRO RCT.

Accuracy of a Risk Alert Threshold for ICU Hypoglycemia: Retrospective Analysis of Alert Performance and Association With Clinical Deterioration Events.

Objectives: To quantify the accuracy of and clinical events associated with a risk alert threshold for impending hypoglycemia during ICU admissions.

Design: Retrospective electronic health record review of clinical events occurring greater than or equal to 1 and less than or equal to 12 hours after the hypoglycemia risk alert threshold was met.

Setting: Adult ICU admissions from June 2020 through April 2021 at the University of Virginia Medical Center.

Proximity to fatal accidents predicts police citation rates on urban and rural roads.

Police enforcement can effectively deter risky driving behaviors and reduce traffic fatalities, including speed-related fatalities. Unlike other areas of data-driven policing, spatial methods to improve road safety are not well-described. The objectives of this study were as follows: (1) determine if proximity to a prior roadway fatality increases the risk of a traffic citation being issued after adjusting for relevant roadway variables; (2) determine if this effect varies between rural and urban roads.

Evaluation of mechanism of injury criteria for field triage of occupants involved in motor vehicle collisions.

Objective: The mechanism of injury (MOI) criteria assist in determining which patients are at high risk of severe injury and would benefit from direct transport to a trauma center. The goal of this study was to determine whether the prognostic performance of the Centers for Disease Control's (CDC) MOI criteria for motor vehicle collisions (MVCs) has changed during the decade since the guidelines were approved. Secondary objectives were to evaluate the performance of these criteria for different age groups and evaluate potential criteria that are not currently in the guidelines.

Partitioning macroscale and microscale ecological processes using covariate-driven non-stationary spatial models.

Ecological inference requires integrating information across scales. This integration creates a complex spatial dependence structure that is most accurately represented by fully non-stationary models. However, ecologists rarely use these models because they are difficult to estimate and interpret.