6 citations · 9 across the 15 of their papers we have counts for
6 papers · 1 filter
A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis
Ciaran Bench, Oskar Pfeffer, Vivek Desai +7
In principle, deep learning models trained on medical time-series, including wearable photoplethysmography (PPG) sensor data, can provide a means to continuously monitor physiologi…
Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks
Ciaran Bench, Vivek Desai, Mohammad Moulaeifard +3
Photoplethysmography (PPG) signals encode information about relative changes in blood volume that can be used to assess various aspects of cardiac health non-invasively, e.g.\ to d…
Quantifying the uncertainty of model-based synthetic image quality metrics
Ciaran Bench, Spencer A. Thomas
The quality of synthetically generated images (e.g. those produced by diffusion models) are often evaluated using information about image contents encoded by pretrained auxiliary m…
Style transfer as data augmentation: evaluating unpaired image-to-image translation models in mammography
Emir Ahmed, Spencer A. Thomas, Ciaran Bench
Several studies indicate that deep learning models can learn to detect breast cancer from mammograms (X-ray images of the breasts). However, challenges with overfitting and poor ge…
Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches
Mohammad Moulaeifard, Loic Coquelin, Mantas Rinkevičius +13
Photoplethysmography (PPG) is a widely used non-invasive physiological sensing technique, suitable for various clinical applications. Such clinical applications are increasingly su…
Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios
Ciaran Bench, Emir Ahmed, Spencer A. Thomas
Mammographic screening is an effective method for detecting breast cancer, facilitating early diagnosis. However, the current need to manually inspect images places a heavy burden…