2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Limitations of Public Chest Radiography Datasets for Artificial Intelligence: Label Quality, Domain Shift, Bias and Evaluation Challenges
Amy Rafferty, Ajitha Rajan
Artificial intelligence has shown significant promise in chest radiography, where deep learning models can approach radiologist-level diagnostic performance. Progress has been acce…
A Selective Quantization Tuner for ONNX Models
Nikolaos Louloudakis, Ajitha Rajan
Quantization reduces the precision of deep neural networks to lower model size and computational demands, but often at the expense of accuracy. Fully quantized models can suffer si…
DiTOX: Fault Detection and Localization in the ONNX Optimizer
Nikolaos Louloudakis, Ajitha Rajan
The ONNX Optimizer, part of the official ONNX repository and widely adopted for graph-level model optimizations, is used by default to optimize ONNX models. Despite its popularity,…
Leveraging Expert Input for Robust and Explainable AI-Assisted Lung Cancer Detection in Chest X-rays
Amy Rafferty, Rishi Ramaesh, Ajitha Rajan
Deep learning models show significant potential for advancing AI-assisted medical diagnostics, particularly in detecting lung cancer through medical image modalities such as chest…