Estimating Uncertainty in Deep Learning for Reporting Confidence to Clinicians when Segmenting Nuclei Image Data. - Biraja Ghoshal; Allan Tucker; Bal Sanghera; Wai Lup Wong (CBMS, 2019)

Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics. - Biraja Ghoshal; Cecilia Lindskog; Allan Tucker (IDA, 2020)

Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection. - Biraja Ghoshal; Allan Tucker (CoRR, 2020)

Uncertainty Estimation in SARS-CoV-2 B-Cell Epitope Prediction for Vaccine Development. - Bhargab Ghoshal; Biraja Ghoshal; Stephen Swift; Allan Tucker (AIME, 2021)

Bayesian Deep Active Learning for Medical Image Analysis. - Biraja Ghoshal; Stephen Swift; Allan Tucker (AIME, 2021)

On Cost-Sensitive Calibrated Uncertainty in Deep Learning: An application on COVID-19 detection. - Biraja Ghoshal; Allan Tucker (CBMS, 2021)

Hyperspherical Weight Uncertainty in Neural Networks. - Biraja Ghoshal; Allan Tucker (IDA, 2021)

Estimating uncertainty in deep learning for reporting confidence to clinicians in medical image segmentation and diseases detection. - Biraja Ghoshal; Allan Tucker; Bal Sanghera; Wai Lup Wong (Comput. Intell., 2021)

Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Grading. - Biraja Ghoshal; Bhargab Ghoshal; Allan Tucker (MIUA, 2022)

On Calibrated Model Uncertainty in Deep Learning. - Biraja Ghoshal; Allan Tucker (CoRR, 2022)

Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. - Biraja Ghoshal; William Woof; Bernardo Mendes; Saoud Al-Khuzaei; Thales Antonio Cabral De Guimaraes; Malena Daich Varela; Yichen Liu; Sagnik Sen 003; Siying Lin; Mital Shah; Yu Fujinami-Yokokawa; Andrew R. Webster; et al. (UNSURE@MICCAI, 2024)