Roselyne Tchoua
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View article: 313 Data-Driven Evaluation of Community Health Worker Program
313 Data-Driven Evaluation of Community Health Worker Program Open
OBJECTIVES/GOALS: Thiswork is an evidential study that demonstrates the positive impactof integrating Community Health Workers (CHWs) and SocialDeterminants of Health on an important health outcome, notably in decreasing the 30-day unplann…
View article: 322 Exploring the Iterative Clustering for Subtype Discovery (iKCAT) Algorithm for Robust Computer-Aided Diagnosis of Lung Cancer
322 Exploring the Iterative Clustering for Subtype Discovery (iKCAT) Algorithm for Robust Computer-Aided Diagnosis of Lung Cancer Open
OBJECTIVES/GOALS: With a growing intеrеst in tailoring disеasе diagnosis to еach individual as opposеd to a “onе-sizе-fits-all” approach, our aim is to еnhancе thе robustnеss of thе Itеrativе Clustеring for Subtypе Discovеry (iKCAT) algori…
View article: 318 Discovering Subgroups with Supervised Machine Learning Models for Heterogeneity of Treatment Effect Analysis
318 Discovering Subgroups with Supervised Machine Learning Models for Heterogeneity of Treatment Effect Analysis Open
OBJECTIVES/GOALS: The goal of the study is to provide insights into the use of machine learning methods as a means to predict heterogeneity of treatment effect (HTE) in participants of randomized clinical trials. METHODS/STUDY POPULATION: …
View article: 313 Data-Driven Evaluation of Community Health Worker Program – CORRIGENDUM
313 Data-Driven Evaluation of Community Health Worker Program – CORRIGENDUM Open
[This corrects the article DOI: 10.1017/cts.2024.284.].
View article: Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models
Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models Open
Classical machine learning and deep learning models for Computer-Aided Diagnosis (CAD) commonly focus on overall classification performance, treating misclassification errors (false negatives and false positives) equally during training. T…
View article: Biomedical heterogeneous data categorization and schema mapping toward data integration
Biomedical heterogeneous data categorization and schema mapping toward data integration Open
Data integration is a well-motivated problem in the clinical data science domain. Availability of patient data, reference clinical cases, and datasets for research have the potential to advance the healthcare industry. However, the unstruc…
View article: Text Summarization towards Scientific Information Extraction
Text Summarization towards Scientific Information Extraction Open
Despite the exponential growth in scientific textual content, research publications are still the primary means for disseminating vital discoveries to experts within their respective fields. These texts are predominantly written for human …
View article: Failure Sources in Machine Learning for Medicine—A Study
Failure Sources in Machine Learning for Medicine—A Study Open
Machine learning (ML) inherently suffers from at least a small amount of inaccuracy. Typically, these errors are acceptable in trade for either speed to an answer or the ability to find an answer at all. For high consequence domains, such …
View article: CompNet: A Designated Model to Handle Combinations of Images and Designed features
CompNet: A Designated Model to Handle Combinations of Images and Designed features Open
Convolutional neural networks (CNNs) are one of the most popular models of Artificial Neural Networks (ANN)s in Computer Vision (CV). A variety of CNN-based structures were developed by researchers to solve problems like image classificati…
View article: Hybrid Human-Machine Scientific Information Extraction
Hybrid Human-Machine Scientific Information Extraction Open
A wealth of valuable research data is locked within the millions of research articles published every year. Reading and extracting pertinent information from those articles has become an unmanageable task for scientists. Moreover, these da…
View article: Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications
Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications Open
In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods rely on machine learning (ML) algorithms to approximate im…
View article: Blending Education and Polymer Science: Semiautomated Creation of a Thermodynamic Property Database
Blending Education and Polymer Science: Semiautomated Creation of a Thermodynamic Property Database Open
Structured databases of chemical and physical properties play a central role in the everyday research activities of scientists and engineers. In materials science, researchers and engineers turn to these databases to quickly query, compare…
View article: A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature
A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature Open
These posters describe a use of information extraction and crowdsourcing to populate a database of polymer properties.
View article: CHIMaD-Poster-Roselyne-2015.pptx
CHIMaD-Poster-Roselyne-2015.pptx Open
These posters describe a use of information extraction and crowdsourcing to populate a database of polymer properties.
View article: A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature
A Hybrid Human-Computer Approach to the Extraction of Scientific Facts from the Literature Open
These posters describe a use of information extraction and crowdsourcing to populate a database of polymer properties.