Fernando Soares Schlindwein

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University of Leicester

United Kingdom

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Improving target identification for catheter ablation using dominant frequency analysis

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Articles (13)

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2024

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2024

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2024

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2023

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2022

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2020

Collaborators (9)

Moloy Das

Newcastle University

UNITED KINGDOM

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Neil Herring

University of Oxford

UNITED KINGDOM

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Ivan Tyukin

Professor of Mathematical Data Science and Modelling

King’s College London

UNITED KINGDOM

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David Koeckerling

University Hospital Heidelberg

GERMANY

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G Andre Ng

University of Leicester

UNITED KINGDOM

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Tim Pearce

Head of Biomedical Engineering Research Group

University of Leicester

UNITED KINGDOM

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Xin Li

Lecturer

University of Leicester

UNITED KINGDOM

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Zheheng Jiang

University of Lancaster

UNITED KINGDOM

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Maria S Guillem

Assistant Professor

Universitat Politècnica de València

SPAIN

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Fernando Soares Schlindwein

Research Interests

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Contact this professor

Recent Grants

Articles (13)

Compressed Deep Learning Models for Wearable Atrial Fibrillation Detection through Attention

ECGVEDNET: A Variational Encoder-Decoder Network for ECG Delineation in Morphology Variant ECGs

Artificial intelligence for ventricular arrhythmia capability using ambulatory electrocardiograms

Correction: Mäkynen et al. Wearable Devices Combined with Artificial Intelligence—A Future Technology for Atrial Fibrillation Detection? Sensors 2022, 22, 8588

Machine learning in sudden cardiac death risk prediction: a systematic review

Evaluating spatial disparities of rotor sites and high dominant frequency regions during catheter ablation for PersAF patients targeting high dominant frequency sites using non-contacting mapping

Simultaneous Whole-Chamber Non-contact Mapping of Highest Dominant Frequency Sites During Persistent Atrial Fibrillation: A Prospective Ablation Study

Rationale and study design of the MINERVA study: Multicentre Investigation of Novel Electrocardiogram Risk markers in Ventricular Arrhythmia prediction-UK multicentre collaboration.

Wearable Devices Combined with Artificial Intelligence—A Future Technology for Atrial Fibrillation Detection?

Automatic Extraction of Recurrent Patterns of High Dominant Frequency Mapping During Human Persistent Atrial Fibrillation.

Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value

Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation

A portable electrocardiogram for real-time monitoring of cardiac signals

Collaborators (9)

Moloy Das

Neil Herring

Ivan Tyukin

David Koeckerling

G Andre Ng

Tim Pearce

Xin Li

Zheheng Jiang

Maria S Guillem

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