1 citations · 2 across the 6 of their papers we have counts for
6 papers
Synthetic Data in Radiological Imaging: Current State and Future Outlook
Elena Sizikova, Andreu Badal, Jana G. Delfino +6
A key challenge for the development and deployment of artificial intelligence (AI) solutions in radiology is solving the associated data limitations. Obtaining sufficient and repre…
Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control
Ghada Zamzmi, Kesavan Venkatesh, Brandon Nelson +4
Background: Machine learning (ML) methods often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices in clinical sett…
Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric Chest X-ray images
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang +3
Model initialization techniques are vital for improving the performance and reliability of deep learning models in medical computer vision applications. While much literature exist…
Semantically Redundant Training Data Removal and Deep Model Classification Performance: A Study with Chest X-rays
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang +3
Deep learning (DL) has demonstrated its innate capacity to independently learn hierarchical features from complex and multi-dimensional data. A common understanding is that its per…
Does image resolution impact chest X-ray based fine-grained Tuberculosis-consistent lesion segmentation?
Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi +2
Deep learning (DL) models are state-of-the-art in segmenting anatomical and disease regions of interest (ROIs) in medical images. Particularly, a large number of DL-based technique…
Data-Centric AI Requires Rethinking Data Notion
Mustafa Hajij, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy +1
The transition towards data-centric AI requires revisiting data notions from mathematical and implementational standpoints to obtain unified data-centric machine learning packages.…