Liam Butler
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Coupled Multivariate Analyses Reveal Separate Climate and Local Drivers of Temporal and Spatial Change in a Coastal Marine Ecosystem Open
Extensive temporal and spatial monitoring data provide an opportunity to identify the drivers of ecosystem change and to understand spatial relationships useful to conservation and management. Such data can potentially overcome the conside…
Survival Estimates of Endangered Shortnose Sturgeon (Acipenser brevirostrum Lesueur, 1818) from Geographically Disjunct Population Segments Open
The complex life history and stock structure of endangered shortnose sturgeon (Acipenser brevirostrum) may hinder recovery efforts for individually managed river populations in the US. Reliable survival estimates are essential for evaluati…
A systemic examination of ecological influences on children prenatally exposed to cocaine. Open
A systemic examination of ecological influences on children prenatally exposed to cocaine.
View article: ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure
ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure Open
AIMS: Heart failure (HF) is a leading cause of death. Early intervention is the key to reduce HF-related morbidity and mortality. This study assesses the utility of electrocardiograms (ECGs) in HF risk prediction. METHODS AND RESULTS: Data…
Testing the Vogt-Bailey Index using task-based fMRI across pulse sequence protocols Open
Local connectivity analyses in fMRI such as the Vogt-Bailey Index, investigate the prevalence of co-fluctuations in the time-series of adjacent voxels. While there have been in silico assessments of the VB Index, this technique has not yet…
View article: Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study
Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study Open
Background: Fatal coronary heart disease (FCHD) affects ~650,000 people yearly in the US. Electrocardiographic artificial intelligence (ECG-AI) models can predict adverse coronary events, yet their application to FCHD is understudied. Obje…
Electrocardiographic Sex Index: A Continuous Representation of Sex Open
Clinical risk calculators consider sex as a binary variable. However, sex is a complex trait with a variety of anatomic, physiologic and metabolic attributes that are not easily summarized with a binary variable [1]. We propose a continuou…
Artificial intelligence and species distribution ensemble models inform resource interactions with offshore wind development Open
Development of offshore wind energy resources has led to growing concerns for marine wildlife. However, significant uncertainty remains regarding the technology’s potential to impact species of interest that may occupy planned development …
Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs Open
Risk of FCHD can be predicted from single-lead ECGs obtained from wearable devices and are statistically concordant with lead I of a 12-lead ECG.
AI-based preeclampsia detection and prediction with electrocardiogram data Open
Introduction More than 76,000 women die yearly from preeclampsia and hypertensive disorders of pregnancy. Early diagnosis and management of preeclampsia can improve outcomes for both mother and baby. In this study, we developed artificial …
Electrocardiographic artificial intelligence model for timely detection of preeclampsia Open
Background/Introduction Preeclampsia (PE) is a major concern for maternal and fetal health, affecting about 5%-8% of women worldwide. Assessing PE early remains an obstetric challenge. PE increases risk of cardiovascular diseases such as h…
Monitoring and Assessment of Buckling in Slender Members with Varying Lateral Restraint and Thermal Loading Using Distributed Sensing Open
Buckling of slender members due to gravity loading or thermal effects is influenced by the member’s geometric imperfections, boundary conditions, and intermediate lateral supports. When assessing the capacity of such members, these paramet…
Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease Open
Background Sudden cardiac death (SCD) affects >4 million people globally, and ∽300,000 yearly in the US. Fatal coronary heart disease (FCHD) is used as a proxy to SCD when coronary disease is present and no other causes of death can be ide…
FEASIBILITY OF REMOTE MONITORING FOR FATAL CORONARY HEART DISEASE FROM SINGLE LEAD ECG Open
Fatal Coronary Heart Disease (FCHD) is a proxy for sudden cardiac death (SCD), affecting >17 million people/year globally, with high prevalence even in younger adults. Electrocardiographic Artificial Intelligence (ECG-AI) models assessing …
Externally validated deep learning model to identify prodromal Parkinson’s disease from electrocardiogram Open
Little is known about electrocardiogram (ECG) markers of Parkinson’s disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk…
Externally Validated Deep Learning Model to Identify Prodromal Parkinson’s Disease from Electrocardiogram Open
Little is known about Electrocardiogram (ECG) markers of Parkinson’s disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk…
National‐scale predictions of plant assemblages via community distribution models: Leveraging published data to guide future surveys Open
Species distribution models (SDMs) have been widely used to create maps of expected species incidence, often using citizen science (CS) occurrence data as inputs. Environmental policy is informed by knowledge of community distributions, bu…
Digital twinning of self-sensing structures using the statistical finite element method Open
The monitoring of infrastructure assets using sensor networks is becoming increasingly prevalent. A digital twin in the form of a finite element (FE) model, as commonly used in design and construction, can help make sense of the copious am…