Search Results for author:
Found 11 papers, 0 papers with code
Virtual Pre-Service Teacher Assessment and Feedback via Conversational Agents
Conversational agents and assistants have been used for decades to facilitate learning.
Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation
Eosinophilic Esophagitis (EoE) represents a challenging condition for medical providers today.
Uncertainty Quantification for Eosinophil Segmentation
The uncertainty can be visualized in an output image to evaluate model performance, provide insight to how deep learning algorithms function, and assist pathologists in identifying eosinophils.
The intersection of video capsule endoscopy and artificial intelligence: addressing unique challenges using machine learning
Discussion: Each of these five challenges is addressed, in part, by one of our AI-based models.
Vital Measurements of Hospitalized COVID-19 Patients as a Predictor of Long COVID: An EHR-based Cohort Study from the RECOVER Program in N3C
It is shown that various symptoms could remain in the stage of post-acute sequelae of SARS-CoV-2 infection (PASC), otherwise known as Long COVID.
Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos
In this paper, we propose an end-to-end temporal abnormality localization for long WCE videos using only weak video level labels.
Unsupervised Shot Boundary Detection for Temporal Segmentation of Long Capsule Endoscopy Videos
However, the search for temporal boundaries in a long video using high dimensional frame-feature matrix is computationally prohibitive and impracticable for real clinical application.
Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video
Automating the detection of frames containing specific lesion in WCE video would relieve gastroenterologists the arduous task of reviewing the entire video before making diagnosis.
Improving Classification through Weak Supervision in Context-specific Conversational Agent Development for Teacher Education
We propose using probabilistic modeling of annotator labeling to generate active learning examples to further label the data.
Hand-drawn Symbol Recognition of Surgical Flowsheet Graphs with Deep Image Segmentation
Perioperative data are essential to investigating the causes of adverse surgical outcomes.
HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach
Image classification is central to the big data revolution in medicine.
