Conference Paper/Proceeding/Abstract 741 views 125 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
Abstract
Machine learning approaches in for prediction of 1-year risk of major bleeding events in anticoagulated atrial fibrillation patients with atrial fibrillation in Wales.
Published in: | ESC Heart & Stroke 2020 |
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Published: |
Barcelona
2020
|
Online Access: |
https://escheart-stroke2020.org/programme/ |
URI: | https://cronfa.swan.ac.uk/Record/cronfa53813 |
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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 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 HDAT 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 Health Data Science COLLEGE CODE HDAT 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 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 |
hierarchytype |
|
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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facultyofmedicinehealthandlifesciences |
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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 |
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https://escheart-stroke2020.org/programme/ |
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2020-01-24T04:06:58Z |
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