Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.

Torabi, Fatemeh; Lacey, Arron; Akbari, Ashley; Harris, Daniel; Lyons, Ronan; Halcox, Julian; Gravenor, Michael

doi:10.13140/RG.2.2.14854.11840

Conference Paper/Proceeding/Abstract 891 views 136 downloads

Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.

Fatemeh Torabi

, Arron Lacey

, Ashley Akbari

, Daniel Harris, Ronan Lyons

, Julian Halcox

, Michael Gravenor

ESC Heart & Stroke 2020

Swansea University Authors: Fatemeh Torabi , Arron Lacey , Ashley Akbari , Daniel Harris, Ronan Lyons , Julian Halcox , Michael Gravenor

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DOI (Published version): 10.13140/RG.2.2.14854.11840

Published in:	ESC Heart & Stroke 2020
Published:	Barcelona 2020
Online Access:	https://escheart-stroke2020.org/programme/
URI:	https://cronfa.swan.ac.uk/Record/cronfa53813

first_indexed	2020-03-12T19:40:56Z
last_indexed	2020-10-10T03:08:00Z
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spelling	2020-10-09T19:20:37.6058176 v2 53813 2020-01-24 Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales. f569591e1bfb0e405b8091f99fec45d3 0000-0002-5853-4625 Fatemeh Torabi Fatemeh Torabi true false b69d245574e754d2637cc9e76379fe11 0000-0001-7983-8073 Arron Lacey Arron Lacey true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false e60c9c73b645f0e8033ae26fa8e634b8 Daniel Harris Daniel Harris true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 3676f695eeda169d0f8c618adf27c04b 0000-0001-6926-2947 Julian Halcox Julian Halcox true false 70a544476ce62ba78502ce463c2500d6 0000-0003-0710-0947 Michael Gravenor Michael Gravenor true false 2020-01-24 MEDS Conference Paper/Proceeding/Abstract ESC Heart & Stroke 2020 Barcelona 24 1 2020 2020-01-24 10.13140/RG.2.2.14854.11840 https://escheart-stroke2020.org/programme/ COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University 2020-10-09T19:20:37.6058176 2020-01-24T00:00:00.0000000 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Fatemeh Torabi 0000-0002-5853-4625 1 Arron Lacey 0000-0001-7983-8073 2 Ashley Akbari 0000-0003-0814-0801 3 Daniel Harris 4 Ronan Lyons 0000-0001-5225-000X 5 Julian Halcox 0000-0001-6926-2947 6 Michael Gravenor 0000-0003-0710-0947 7 53813__16839__0cd85122692544dd8d8b5105dffd2bf6.pdf Poster-HASBLED-20200114.pdf 2020-03-12T12:50:42.2608505 Output 1099209 application/pdf Author's Original true true eng
title	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
spellingShingle	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales. Fatemeh Torabi Arron Lacey Ashley Akbari Daniel Harris Ronan Lyons Julian Halcox Michael Gravenor
title_short	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
title_full	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
title_fullStr	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
title_full_unstemmed	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
title_sort	Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
author_id_str_mv	f569591e1bfb0e405b8091f99fec45d3 b69d245574e754d2637cc9e76379fe11 aa1b025ec0243f708bb5eb0a93d6fb52 e60c9c73b645f0e8033ae26fa8e634b8 83efcf2a9dfcf8b55586999d3d152ac6 3676f695eeda169d0f8c618adf27c04b 70a544476ce62ba78502ce463c2500d6
author_id_fullname_str_mv	f569591e1bfb0e405b8091f99fec45d3_*_Fatemeh Torabi b69d245574e754d2637cc9e76379fe11__Arron Lacey aa1b025ec0243f708bb5eb0a93d6fb52__Ashley Akbari e60c9c73b645f0e8033ae26fa8e634b8__Daniel Harris 83efcf2a9dfcf8b55586999d3d152ac6__Ronan Lyons 3676f695eeda169d0f8c618adf27c04b__Julian Halcox 70a544476ce62ba78502ce463c2500d6_**_Michael Gravenor
author	Fatemeh Torabi Arron Lacey Ashley Akbari Daniel Harris Ronan Lyons Julian Halcox Michael Gravenor
author2	Fatemeh Torabi Arron Lacey Ashley Akbari Daniel Harris Ronan Lyons Julian Halcox Michael Gravenor
format	Conference Paper/Proceeding/Abstract
container_title	ESC Heart & Stroke 2020
publishDate	2020
institution	Swansea University
doi_str_mv	10.13140/RG.2.2.14854.11840
college_str	Faculty of Medicine, Health and Life Sciences
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hierarchy_parent_title	Faculty of Medicine, Health and Life Sciences
department_str	Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
url	https://escheart-stroke2020.org/programme/
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published_date	2020-01-24T02:05:40Z
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Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.

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