[HTML][HTML] Artificial intelligence in cardiac MRI: is clinical adoption forthcoming?
Artificial intelligence (AI) refers to the area of knowledge that develops computerised models
to perform tasks that typically require human intelligence. These algorithms are programmed …
to perform tasks that typically require human intelligence. These algorithms are programmed …
Interpretability benchmark for evaluating spatial misalignment of prototypical parts explanations
Prototypical parts-based networks are becoming increasingly popular due to their faithful
self-explanations. However, their similarity maps are calculated in the penultimate network …
self-explanations. However, their similarity maps are calculated in the penultimate network …
Explaining chest x-ray pathologies in natural language
Most deep learning algorithms lack explanations for their predictions, which limits their
deployment in clinical practice. Approaches to improve explainability, especially in medical …
deployment in clinical practice. Approaches to improve explainability, especially in medical …
[HTML][HTML] A multimodal deep learning model for cardiac resynchronisation therapy response prediction
E Puyol-Antón, BS Sidhu, J Gould, B Porter… - Medical image …, 2022 - Elsevier
We present a novel multimodal deep learning framework for cardiac resynchronisation
therapy (CRT) response prediction from 2D echocardiography and cardiac magnetic …
therapy (CRT) response prediction from 2D echocardiography and cardiac magnetic …
CT-guided survival prediction of esophageal cancer
Z Lin, W Cai, W Hou, Y Chen, B Gao… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Survival prediction of esophageal cancer is an essential task for doctors to make
personalized cancer treatment plans. However, handcrafted features from medical images …
personalized cancer treatment plans. However, handcrafted features from medical images …
Protopshare: Prototype sharing for interpretable image classification and similarity discovery
In this paper, we introduce ProtoPShare, a self-explained method that incorporates the
paradigm of prototypical parts to explain its predictions. The main novelty of the ProtoPShare …
paradigm of prototypical parts to explain its predictions. The main novelty of the ProtoPShare …
3d brain and heart volume generative models: A survey
Generative models such as generative adversarial networks and autoencoders have gained
a great deal of attention in the medical field due to their excellent data generation capability …
a great deal of attention in the medical field due to their excellent data generation capability …
[HTML][HTML] Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images
Quantifying uncertainty of predictions has been identified as one way to develop more
trustworthy artificial intelligence (AI) models beyond conventional reporting of performance …
trustworthy artificial intelligence (AI) models beyond conventional reporting of performance …
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
Recent advancements in AI applications to healthcare have shown incredible promise in
surpassing human performance in diagnosis and disease prognosis. With the increasing …
surpassing human performance in diagnosis and disease prognosis. With the increasing …
[HTML][HTML] Artificial intelligence to improve risk prediction with nuclear cardiac studies
Abstract Purpose of Review As machine learning-based artificial intelligence (AI) continues
to revolutionize the way in which we analyze data, the field of nuclear cardiology provides …
to revolutionize the way in which we analyze data, the field of nuclear cardiology provides …