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 …

Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment

PC Tripathi, S Tabakhi, MNI Suvon, L Schöb… - arXiv preprint arXiv …, 2024 - arxiv.org
Pulmonary Arterial Wedge Pressure (PAWP) is an essential cardiovascular hemodynamics
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

K Lekadir, R Osuala, C Gallin, N Lazrak… - arXiv preprint arXiv …, 2021 - academia.edu
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 …

Interpretable thoracic pathologic prediction via learning group-disentangled representation

H Li, Y Wu, H Hu, H Lu, Q Huang, S Wan - Methods, 2023 - Elsevier
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 …

Uncertainty-aware training for cardiac resynchronisation therapy response prediction

T Dawood, C Chen, R Andlauer, BS Sidhu… - … Workshop on Statistical …, 2021 - Springer
Abstract Evaluation of predictive deep learning (DL) models beyond conventional
performance metrics has become increasingly important for applications in sensitive …

GDRL: An interpretable framework for thoracic pathologic prediction

Y Wu, H Li, X Feng, A Casanova, AF Abate… - Pattern Recognition …, 2023 - Elsevier
Deep learning methods have shown significant performance in medical image analysis
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

Z Yuan, E Puyol-Antón, H Jogeesvaran, B Inusa… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Learning Group-Disentangled Representation for Interpretable Thoracic Pathologic Prediction

H Li, Y Wu, H Hu, H Lu, Y Lai… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Deep learning methods have shown significant performance in medical image analysis
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 …

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 …