[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …
respect to the quantity of high-performing solutions reported in the literature. End users are …
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
The comprehensive integration of machine learning healthcare models within clinical
practice remains suboptimal, notwithstanding the proliferation of high-performing solutions …
practice remains suboptimal, notwithstanding the proliferation of high-performing solutions …
Test time augmentation meets post-hoc calibration: uncertainty quantification under real-world conditions
Communicating the predictive uncertainty of deep neural networks transparently and reliably
is important in many safety-critical applications such as medicine. However, modern neural …
is important in many safety-critical applications such as medicine. However, modern neural …
[HTML][HTML] Quantifying deep neural network uncertainty for atrial fibrillation detection with limited labels
Atrial fibrillation (AF) is the most common arrhythmia found in the intensive care unit (ICU),
and is associated with many adverse outcomes. Effective handling of AF and similar …
and is associated with many adverse outcomes. Effective handling of AF and similar …
iPCa-Net: A CNN-based framework for predicting incidental prostate cancer using multiparametric MRI
L Wen, S Wang, X Pan, Y Liu - Computerized Medical Imaging and …, 2023 - Elsevier
Incidental prostate cancer (iPCa) is an early stage of clinically significant prostate cancer
(csPCa) and is typically asymptomatic, making it difficult to detect in clinical practice. The …
(csPCa) and is typically asymptomatic, making it difficult to detect in clinical practice. The …
Training deep neural networks with noisy clinical labels: toward accurate detection of prostate cancer in US data
Purpose: Ultrasound is the standard-of-care to guide the systematic biopsy of the prostate.
During the biopsy procedure, up to 12 biopsy cores are randomly sampled from six zones …
During the biopsy procedure, up to 12 biopsy cores are randomly sampled from six zones …
Toward confident prostate cancer detection using ultrasound: a multi-center study
Purpose Deep learning-based analysis of micro-ultrasound images to detect cancerous
lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model …
lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model …
Semi-supervised learning from coarse histopathology labels
Ultrasound imaging is commonly used to guide sampling the prostate tissue in transrectal
biopsies, followed by detection of cancer through histopathological analysis and coarse …
biopsies, followed by detection of cancer through histopathological analysis and coarse …