AI and Big Data in Cardiology
A Practical Guide
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Chapter and Conference Paper
Assessment of the Evolution of Temporal Segmental Strain in a Longitudinal Study of Myocardial Infarction
In this study, we propose an approach for the assessment of the evolution of heart function in a population of ST-elevation myocardial infarction (STEMI) patients. The patients were imaged using cine MRI with ...
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Chapter
Introduction
This chapter acts as an introduction to some of the key terms and concepts that are necessary to understand the subsequent chapters. The terms artificial intelligence (AI), machine learning and deep learning a...
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Chapter
Conclusions
This chapter reviews the preceding chapters and attempts to highlight common themes and important take-home messages for the future of artificial intelligence (AI) in cardiology. We attempt to look into the fu...
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Chapter and Conference Paper
Which Anatomical Directions to Quantify Local Right Ventricular Strain in 3D Echocardiography?
Technological advances in image quality and post-processing have led to the better clinical adoption of 3D echocardiography to quantify cardiac function. However, the right ventricle (RV) raises specific chall...
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Chapter and Conference Paper
Localizing Cardiac Dyssynchrony in M-mode Echocardiography with Attention Maps
Cardiac Resynchronization Therapy (CRT) is a treatment aimed at restoring the electrical synchronization in patients with heart failure and intraventricular conduction delay. However, over 30% of patients do n...
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Chapter and Conference Paper
Strainger Things: Discrete Differential Geometry for Transporting Right Ventricular Deformation Across Meshes
Cardiac dynamics have been a focus of image analysis, and their statistical models are used in a wide range of applications: generating synthetic datasets, derivation of specific biomarkers of pathologies, or ...
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Chapter
Analysis of Non-imaging Data
Whilst most of this book has focused on imaging data because of the key role it plays in cardiology, non-imaging data also has an important role to play. This chapter reviews some of the most relevant non-imag...
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Chapter
AI and Machine Learning: The Basics
In this chapter the key concepts of artificial intelligence and machine learning are introduced. The importance of first identifying and defining the right problem is emphasised. A review is provided of differ...
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Chapter
Outcome Prediction
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 treatment. A clinical opinion piece ...
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Book
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Chapter
From Machine Learning to Deep Learning
This chapter provides a thorough grounding in the fundamental mathematical concepts of deep learning. It is first shown how a simple linear classifier can be defined based on the equation for a straight line. ...
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Chapter
Diagnosis
This covers the clinical application of diagnosis of cardiovascular disease. A clinical opinion piece discusses the current clinical standard for diagnosis tasks and its limitations. The technical review sum...
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Book and Conference Proceedings
Functional Imaging and Modeling of the Heart
12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, Proceedings
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Chapter and Conference Paper
Characterizing Myocardial Ischemia and Reperfusion Patterns with Hierarchical Manifold Learning
We aim at better understanding the mechanisms of ischemia and reperfusion, in the context of acute myocardial infarction. For this purpose, imaging and in particular magnetic resonance imaging are of great val...
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Chapter and Conference Paper
Reinforcement Learning for Active Modality Selection During Diagnosis
Diagnosis through imaging generally requires the combination of several modalities. Algorithms for data fusion allow merging information from different sources, mostly combining all images in a single step. In...
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Chapter and Conference Paper
Hierarchical Multi-modality Prediction Model to Assess Obesity-Related Remodelling
The diagnosis of cardiovascular illnesses uses multiple modalities in order to obtain a complete and as robust as possible assessment of the heart. However, when addressing distinct pathologies, not all inform...
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Article
Postoperative ileus after laparoscopic primary and incisional abdominal hernia repair with intraperitoneal mesh (DynaMesh®-IPOM versus Parietex™ Composite): a single institution experience
Laparoscopic primary or incisional abdominal hernia repair with intraperitoneal mesh placement is a well-accepted and safe technique. Evidence for complications however remains inconclusive, and little is know...
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Chapter and Conference Paper
Investigation of the Impact of Normalization on the Study of Interactions Between Myocardial Shape and Deformation
Myocardial shape and deformation are two relevant descriptors for the study of cardiac function and can undergo strong interactions depending on diseases. Manifold learning provides low dimensional representat...
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Chapter and Conference Paper
Population-Based Personalization of Geometric Models of Myocardial Infarction
We propose a strategy to perform population-based personalization of a model, to overcome the limits of case-based personalization for generating virtual populations from models that include randomness. We for...
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Chapter and Conference Paper
Learning Interactions Between Cardiac Shape and Deformation: Application to Pulmonary Hypertension
Cardiac shape and deformation are two relevant descriptors for the characterization of cardiovascular diseases. It is also known that strong interactions exist between them depending on the disease. In clinica...
