Erik Linstead
YOU?
Author Swipe
Integration of an Artificial Intelligence–Based Autism Diagnostic Device into the ECHO Autism Primary Care Workflow: Prospective Observational Study Open
Background Pediatric specialist shortages and rapidly rising autism prevalence rates have compelled primary care clinicians to consider playing a greater role in the autism diagnostic process. The ECHO Autism: Early Diagnosis Program (EDx)…
Development and Application of Self-Supervised Machine Learning for Smoke Plume and Active Fire Identification from the Fire Influence on Regional to Global Environments and Air Quality Datasets Open
Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in …
Development and Application of Self-Supervised Machine Learning for Smoke Plume and Active Fire Identification from the FIREX-AQ Datasets Open
Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in …
Joint modeling of degradation signals and time‐to‐event data for the prediction of remaining useful life Open
Accurate prediction of remaining useful life (RUL) for in‐service systems plays an important role in ensuring efficient operation of industrial equipment and in preventing unexpected equipment failures. In this paper, we present a prognost…
Facilities Usage on the International Space Station Open
Science experiments on the International Space Station (ISS) - and in future space habitats - require“facilities,” as they are known to the space agencies, as the core building blocks of the researchcapabilities they provide. Facilities ar…
What kind of ‘Explainable AI’ do users need? Open
Much attention is currently given to generative artificial intelligence (AI), but most currently available AI technologies consist in so-called decision support systems (DSSs). DSSs are meant to improve the efficiency of human decision-mak…
A generalized machine learning model for long-term coral reef monitoring in the Red Sea Open
Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El N…
What kind of Explainable AI do users need? Open
Artificial intelligence (AI) systems that make predictions, translate text, generate text and images, and much more are ubiquitous in modern life. Such AI systems typically perform tasks that humans cannot perform with the same degree of s…
Enhancing employment outcomes for autistic youth: Using machine learning to identify strategies for success Open
BACKGROUND: The employment rates of autistic young adults continue to be significantly lower than that of their neurotypical peers. OBJECTIVE: Researchers in this study sought to identify the barriers and facilitators associated with these…
Large-Scale Identification and Analysis of Factors Impacting Simple Bug Resolution Times in Open Source Software Repositories Open
One of the most prominent issues the ever-growing open-source software community faces is the abundance of buggy code. Well-established version control systems and repository hosting services such as GitHub and Maven provide a checks-and-b…
Towards QoS-Based Embedded Machine Learning Open
Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applicati…
Applications of Unsupervised Machine Learning in Autism Spectrum Disorder Research: a Review Open
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic a…
A Large-Scale Sentiment Analysis of Tweets Pertaining To The 2020 US Presidential Election Open
We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user acc…
Evaluating the 0–10 Point Pain Scale on Adolescent Opioid Use in US Emergency Departments Open
Objective: To evaluate trends in national emergency department (ED) adolescent opioid use in relation to reported pain scores. Methods: A retrospective, cross-sectional analysis on National Hospital Ambulatory Medical Care Survey (NHAMCS) …
Assessing the Vertical Displacement of the Grand Ethiopian Renaissance Dam during Its Filling Using DInSAR Technology and Its Potential Acute Consequences on the Downstream Countries Open
The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is currently under construction and has been filling at a fast rate without sufficient known analysis on possible impacts on the body of the structure. The f…
Assessing the Vertical Displacement of the Grand Ethiopian Renaissance Dam during its Filling using DInSAR technology and its Potential Acute Consequences on the Downstream Countries Open
The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is currently under construction and has been filling at a fast rate without sufficient known analysis on possible impacts on the body of the structure. The f…
A Quantitative Validation of Multi-Modal Image Fusion and Segmentation for Object Detection and Tracking Open
In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in co…
Racial and ethnic disparities in opioid use for adolescents at US emergency departments Open
Background Racial/ethnic disparities in the use of opioids to treat pain disorders have been previously reported in the emergency department (ED). Further research is needed to better evaluate the impact race/ethnicity may have on the use …
Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study Open
Background Challenging behaviors are prevalent among individuals with autism spectrum disorder; however, research exploring the impact of challenging behaviors on treatment response is lacking. Objective The purpose of this study was to id…
On-Device Deep Learning Inference for System-on-Chip (SoC) Architectures Open
As machine learning becomes ubiquitous, the need to deploy models on real-time, embedded systems will become increasingly critical. This is especially true for deep learning solutions, whose large models pose interesting challenges for tar…
Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study (Preprint) Open
BACKGROUND Challenging behaviors are prevalent among individuals with autism spectrum disorder; however, research exploring the impact of challenging behaviors on treatment response is lacking. OBJECTIVE The purpose of this study was to id…
Association Between Coffee Intake and Incident Heart Failure Risk Open
Background: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk…
Additional file 1 of Racial and ethnic disparities in opioid use for adolescents at US emergency departments Open
Additional file 1.