The role of AI in characterizing the DCM phenotype
C Asher, E Puyol-Antón, M Rizvi, B Ruijsink… - Frontiers in …, 2021 - frontiersin.org
Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and
dysfunction in the absence of coronary disease. Emerging evidence suggests many patients …
dysfunction in the absence of coronary disease. Emerging evidence suggests many patients …
Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment
Pulmonary Arterial Wedge Pressure (PAWP) is an essential cardiovascular hemodynamics
marker to detect heart failure. In clinical practice, Right Heart Catheterization is considered a …
marker to detect heart failure. In clinical practice, Right Heart Catheterization is considered a …
[PDF][PDF] FUTURE-AI: Guiding principles and consensus recommendations for trustworthy artificial intelligence in future medical imaging
The recent advancements in artificial intelligence (AI) combined with the extensive amount
of data generated by today's clinical systems, has led to the development of imaging AI …
of data generated by today's clinical systems, has led to the development of imaging AI …
Interpretable thoracic pathologic prediction via learning group-disentangled representation
Deep learning has brought a significant progress in medical image analysis. However, their
lack of interpretability might bring high risk for wrong diagnosis with limited clinical …
lack of interpretability might bring high risk for wrong diagnosis with limited clinical …
Uncertainty-aware training for cardiac resynchronisation therapy response prediction
Abstract Evaluation of predictive deep learning (DL) models beyond conventional
performance metrics has become increasingly important for applications in sensitive …
performance metrics has become increasingly important for applications in sensitive …
GDRL: An interpretable framework for thoracic pathologic prediction
Deep learning methods have shown significant performance in medical image analysis
tasks. However, they generally act like “black box” without explanations in both feature …
tasks. However, they generally act like “black box” without explanations in both feature …
Deep Learning Framework for Spleen Volume Estimation from 2D Cross-sectional Views
Abnormal spleen enlargement (splenomegaly) is regarded as a clinical indicator for a range
of conditions, including liver disease, cancer and blood diseases. While spleen length …
of conditions, including liver disease, cancer and blood diseases. While spleen length …
Learning Group-Disentangled Representation for Interpretable Thoracic Pathologic Prediction
Deep learning methods have shown significant performance in medical image analysis
tasks. However, they generally act like” black box” without explanations in both feature …
tasks. However, they generally act like” black box” without explanations in both feature …
A Multilabel Dermatologic Classification and Interpretability Study for Small Samples and Extremely Unbalanced Classes
J Tang, L Jiang, F Zheng, X Zhang… - 2024 International …, 2024 - ieeexplore.ieee.org
Early diagnosis of melanoma is important for patient care, but dermatologists are struggling
to keep up with the increasing demand for skin disease care. Computer-aided diagnostic …
to keep up with the increasing demand for skin disease care. Computer-aided diagnostic …
Outcome Prediction
B Ly, M Pop, H Cochet, N Duchateau… - AI and Big Data in …, 2023 - Springer
This chapter focuses on how we can best predict the future health of patients, known as
prognosis. This encompasses areas such as risk prediction and predicting response to …
prognosis. This encompasses areas such as risk prediction and predicting response to …