Donald E. Brown
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View article: Entropy as a marker of physiological transition during pediatric cardiopulmonary exercise testing
Entropy as a marker of physiological transition during pediatric cardiopulmonary exercise testing Open
This research analyzed the sample entropy (SampEn) of breath-by-breath cardiopulmonary exercise testing (CPET) data from 170 healthy pediatric participants (85 males) 8 to 18-years-old, using a Bayesian statistics approach. SampEn measures…
View article: A Bayesian Survival Analysis on Long COVID and Non-Long COVID Patients: A Cohort Study Using National COVID Cohort Collaborative (N3C) Data
A Bayesian Survival Analysis on Long COVID and Non-Long COVID Patients: A Cohort Study Using National COVID Cohort Collaborative (N3C) Data Open
Since the outbreak of the COVID-19 pandemic in 2020, numerous studies have focused on the long-term effects of COVID infection. On 1 October 2021, the Centers for Disease Control (CDC) implemented a new code in the International Classifica…
View article: Using the Moral‐Situational‐Action Model of Extremist Violence (MSA‐EV) to Assess Fluctuating Levels of Risk in Women: The Relevance of Risk, Promotive, and Protective Factors
Using the Moral‐Situational‐Action Model of Extremist Violence (MSA‐EV) to Assess Fluctuating Levels of Risk in Women: The Relevance of Risk, Promotive, and Protective Factors Open
Our research examines the Moral Situational Action Model of Extremist Violence (MSA‐EV) in differentiating radicalized women who are likely to proceed to acts of lethal violence from those who are not using an additional risk, protective, …
View article: Towards Robust Multimodal Representation: A Unified Approach with Adaptive Experts and Alignment
Towards Robust Multimodal Representation: A Unified Approach with Adaptive Experts and Alignment Open
Healthcare relies on multiple types of data, such as medical images, genetic information, and clinical records, to improve diagnosis and treatment. However, missing data is a common challenge due to privacy restrictions, cost, and technica…
View article: Racial and Ethnic and Rural Variations in the Use of Hybrid Prenatal Care in the US
Racial and Ethnic and Rural Variations in the Use of Hybrid Prenatal Care in the US Open
Importance Understanding whether there are racial and ethnic and residential disparities in prenatal telehealth uptake is necessary for ensuring equitable access and guiding implementation of future hybrid (ie, both telehealth and in-perso…
View article: Intraoperative short-term blood pressure variability and postoperative acute kidney injury: a single-center retrospective cohort study using sample entropy analysis
Intraoperative short-term blood pressure variability and postoperative acute kidney injury: a single-center retrospective cohort study using sample entropy analysis Open
Assessment of very short-term blood pressure variability does not improve the discrimination of postoperative acute kidney injury in patients undergoing non-cardiac surgery in this sample.
View article: GenGMM: Generalized Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation
GenGMM: Generalized Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation Open
Domain adaptive semantic segmentation is the task of generating precise and dense predictions for an unlabeled target domain using a model trained on a labeled source domain. While significant efforts have been devoted to improving unsuper…
View article: ERDS: Optimizing Domains Using Observation-Based Extremity
ERDS: Optimizing Domains Using Observation-Based Extremity Open
View article: Dynamics of gas exchange and heart rate signal entropy in standard cardiopulmonary exercise testing during critical periods of growth and development
Dynamics of gas exchange and heart rate signal entropy in standard cardiopulmonary exercise testing during critical periods of growth and development Open
Standard cardiopulmonary exercise testing (CPET) produces a rich dataset but its current analysis is often limited to a few derived variables such as maximal or peak oxygen uptake (V̇O 2 ). We tested whether breath‐by‐breath CPET data could…
View article: Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings
Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings Open
Data from the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) are now widely available. One major computational challenge is dealing with high dimensionality and inherent sparsity, which is typically ad…
View article: ProtoGMM: Multi-prototype Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation
ProtoGMM: Multi-prototype Gaussian-Mixture-based Domain Adaptation Model for Semantic Segmentation Open
Domain adaptive semantic segmentation aims to generate accurate and dense predictions for an unlabeled target domain by leveraging a supervised model trained on a labeled source domain. The prevalent self-training approach involves retrain…
View article: Machine-learning-based integrative –‘omics analyses reveal immunologic and metabolic dysregulation in environmental enteric dysfunction
Machine-learning-based integrative –‘omics analyses reveal immunologic and metabolic dysregulation in environmental enteric dysfunction Open
View article: Bayesian Optimization of Sample Entropy Hyperparameters for Short Time Series
Bayesian Optimization of Sample Entropy Hyperparameters for Short Time Series Open
Quantifying the complexity and irregularity of time series data is a primary pursuit across various data-scientific disciplines. Sample entropy (SampEn) is a widely adopted metric for this purpose, but its reliability is sensitive to the c…
View article: Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries
Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries Open
Background In low-middle income countries, healthcare providers primarily use paper health records for capturing data. Paper health records are utilized predominately due to the prohibitive cost of acquisition and maintenance of automated …
View article: Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation
Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation Open
Eosinophilic Esophagitis (EoE) represents a challenging condition for medical providers today. The cause is currently unknown, the impact on a patient's daily life is significant, and it is increasing in prevalence. Traditional approaches …
View article: Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation
Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation Open
Eosinophilic Esophagitis (EoE) represents a challenging condition for medical providers today. The cause is currently unknown, the impact on a patient's daily life is significant, and it is increasing in prevalence. Traditional approaches …
View article: Joint Representation Learning for Retrieval and Annotation of Genomic Interval Sets
Joint Representation Learning for Retrieval and Annotation of Genomic Interval Sets Open
As available genomic interval data increase in scale, we require fast systems to search them. A common approach is simple string matching to compare a search term to metadata, but this is limited by incomplete or inaccurate annotations. An…
View article: Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning
Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning Open
The multivariate time series classification (MTSC) task aims to predict a class label for a given time series. Recently, modern deep learning-based approaches have achieved promising performance over traditional methods for MTSC tasks. The…
View article: Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT Open
Deep learning for histopathology has been successfully used for disease classification, image segmentation and more. However, combining image and text modalities using current state-of-the-art (SOTA) methods has been a challenge due to the…
View article: Global Analysis with Aggregation-based Beaconing Detection across Large Campus Networks
Global Analysis with Aggregation-based Beaconing Detection across Large Campus Networks Open
We present a new approach to effectively detect and prioritize malicious beaconing activities in large campus networks by profiling the server activities through aggregated signals across multiple traffic protocols and networks. Key compon…
View article: Automatic Report Generation for Histopathology images using pre-trained Vision Transformers
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers Open
Deep learning for histopathology has been successfully used for disease classification, image segmentation and more. However, combining image and text modalities using current state-of-the-art methods has been a challenge due to the high r…
View article: Computer Vision Digitization of Smartphone Images of Anesthesia Paper Health Records from Low-Middle Income Countries
Computer Vision Digitization of Smartphone Images of Anesthesia Paper Health Records from Low-Middle Income Countries Open
Handwritten paper charting remains the primary method of collecting anesthesia health data in low-middle income countries that lack automated data capture devices and electronic medical records. Lack of digital data precludes automated eva…
View article: Computer Vision Digitization of Smartphone Images of Anesthesia Paper Health Records from Low-Middle Income Countries
Computer Vision Digitization of Smartphone Images of Anesthesia Paper Health Records from Low-Middle Income Countries Open
Handwritten paper charting remains the primary method of collecting anesthesia health data in low-middle income countries that lack automated data capture devices and electronic medical records. Lack of digital data precludes automated eva…
View article: Uncertainty Quantification for Eosinophil Segmentation
Uncertainty Quantification for Eosinophil Segmentation Open
Eosinophilic Esophagitis (EoE) is an allergic condition increasing in prevalence. To diagnose EoE, pathologists must find 15 or more eosinophils within a single high-power field (400X magnification). Determining whether or not a patient ha…
View article: Uncertainty Quantification for Eosinophil Segmentation
Uncertainty Quantification for Eosinophil Segmentation Open
Eosinophilic Esophagitis (EoE) is an allergic condition increasing in prevalence. To diagnose EoE, pathologists must find 15 or more eosinophils within a single high-power field (400X magnification). Determining whether or not a patient ha…
View article: Label-efficient Contrastive Learning-based model for nuclei detection and classification in 3D Cardiovascular Immunofluorescent Images
Label-efficient Contrastive Learning-based model for nuclei detection and classification in 3D Cardiovascular Immunofluorescent Images Open
Recently, deep learning-based methods achieved promising performance in nuclei detection and classification applications. However, training deep learning-based methods requires a large amount of pixel-wise annotated data, which is time-con…
View article: The intersection of video capsule endoscopy and artificial intelligence: addressing unique challenges using machine learning
The intersection of video capsule endoscopy and artificial intelligence: addressing unique challenges using machine learning Open
Introduction: Technical burdens and time-intensive review processes limit the practical utility of video capsule endoscopy (VCE). Artificial intelligence (AI) is poised to address these limitations, but the intersection of AI and VCE revea…
View article: Joint representation learning for retrieval and annotation of genomic interval sets
Joint representation learning for retrieval and annotation of genomic interval sets Open
Motivation As available genomic interval data increases in scale, we require fast systems to search it. A common approach is simple string matching to compare a search term to metadata, but this is limited by incomplete or inaccurate annot…
View article: A study of the status of support service programs for Black and Hispanic students in the nation's twenty-eight Jesuit colleges and universities.
A study of the status of support service programs for Black and Hispanic students in the nation's twenty-eight Jesuit colleges and universities. Open
The primary purpose of this study was to determine the extent to which support service programs are available for Black and Hispanic students attending the nation's twenty-eight Jesuit colleges and universities. Where programs existed the …
View article: Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings
Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings Open
Motivation Data from the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is now widely available. One major computational challenge is dealing with high dimensionality and inherent sparsity, which is ty…