Emmanuel Abbé

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Publications associées (43)

Boosted decoders for reed-muller codes

Emmanuel Abbé, Colin Peter Sandon

Various embodiments are directed to Reed-Muller decoding systems and methods configured to decode RM codes by processing each received noisy codeword f of the received RM encoded data to determine therefrom a respective decoding that best fits the noisy co ...

2025

Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography

Emmanuel Abbé

Purpose: This study aimed to evaluate the efficacy of the Chat Generative Pre-trained Transformer (ChatGPT) in guiding the need for invasive coronary angiography (ICA) in high-risk non-ST-elevation (NSTE) acute coronary syndrome (ACS) patients based on bot ...

2024

AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation

Emmanuel Abbé, Ortal Yona Senouf, Thabodhan Mahendiran, Ntorina Thanou, Edward Carlo Giorgio Andò

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional c ...

Elsevier BV2024

Gender Bias in AI's Perception of Cardiovascular Risk

Emmanuel Abbé

The study investigated gender bias in GPT-4's assessment of coronary artery disease risk by presenting identical clinical vignettes of men and women with and without psychiatric comorbidities. Results suggest that psychiatric conditions may influence GPT-4 ...

2024

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction

Pascal Frossard, Emmanuel Abbé, Ortal Yona Senouf, Ntorina Thanou, Ivan-Daniel Sievering

Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI ...

2024

A study of ChatGPT in facilitating Heart Team decisions on severe aortic stenosis

Emmanuel Abbé

BACKGROUND: Multidisciplinary Heart Teams (HTs) play a central role in the management of valvular heart diseases. However, the comprehensive evaluation of patients' data can be hindered by logistical challenges, which in turn may affect the care they recei ...

EUROPA EDITION2024

Can Knowledge Transfer Techniques Compensate for the Limited Myocardial Infarction Data by Leveraging Haemodynamics? An in silico Study

Annalisa Buffa, Simone Deparis, Emmanuel Abbé, Ortal Yona Senouf, Riccardo Tenderini

The goal of this work is to investigate the ability of transfer learning (TL) and multitask learning (MTL) algorithms to predict tasks related to myocardial infarction (MI) in a small-data regime, leveraging a larger dataset of haemodynamic targets. The da ...

Springer Nature2023

Towards AI-assisted cardiology: a reflection on the performance and limitations of using large language models in clinical decision-making

Emmanuel Abbé, Mehdi Ali Gadiri, Ntorina Thanou

Europa Edition2023

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

Emmanuel Abbé, Thabodhan Mahendiran, Olivier Muller, Stéphane Fournier

Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correct ...

Oxford Univ Press2023

Reed-Muller Codes

Emmanuel Abbé

Reed-Muller (RM) codes are among the oldest, simplest and perhaps most ubiquitous family of codes. They are used in many areas of coding theory in both electrical engineering and computer science. Yet, many of their important properties are still under inv ...

NOW PUBLISHERS INC2023

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