AI model predicts injury risk in rugby union
References
| Title | Datblygu model AI cyntaf ar gyfer anafiadau rygbi |
|---|---|
| Degree of recognition | National |
| Media name/outlet | Newyddion S4C |
| Media type | Web |
| Country/Territory | United Kingdom |
| Date | 17/12/24 |
| Description | Mae ymchwilwyr wedi datblygu'r model deallusrwydd artiffisial (AI) cyntaf allai ragweld risg anafiadau i goesau chwaraewyr rygbi. Anafiadau i’r coesau yw'r math mwyaf cyffredin yn rygbi'r undeb, gan gyfrif am hanner y dyddiau sy'n cael eu colli yn y gêm ryngwladol. Er mwyn lleihau'r risg o anafiadau, mae ymchwilwyr o Brifysgol Bangor wedi datblygu model deallusrwydd artiffisial newydd sy'n caniatáu i hyfforddwyr addasu rhai agweddau ar hyfforddiant eu chwaraewyr. Mae'r model yn defnyddio dull dadansoddi adnabod patrymau i nodi'r ffactorau cymhleth sy'n gallu arwain at anafiadau, gan gynnwys troi ffêr, ac achosion mwy difrifol o anafiadau straen i’r cyhyrau. Fel rhan o'r prosiect, roedd yr ymchwilwyr wedi dilyn 36 o chwaraewyr rygbi'r undeb lled-broffesiynol dros ddau dymor. Fe wnaethon nhw ddefnyddio data ar lwyth hyfforddi, profi perfformiad, mesurau goddrychol, sgrinio cyhyrysgerbydol ac anafiadau blaenorol. |
| URL | https://newyddion.s4c.cymru/article/25524 |
| Persons | Julian Owen, Seren Evans |
| Title | AI model predicts injury risk in rugby union |
|---|---|
| Degree of recognition | Regional |
| Media name/outlet | Wales247 |
| Media type | Web |
| Country/Territory | United Kingdom |
| Date | 17/12/24 |
| Description | The first AI model that can predict the risk of non-contact lower limb injury in rugby players has been developed by researchers at Bangor University. The model uses pattern recognition analysis to identify the complex and interconnected factors that can lead to injuries such as sprained ankles, torn or sprained ligaments and more severe muscle strains. Lower limb injuries are the most common type in rugby union, accounting for about half of the days lost due to injury in the international game. |
| URL | https://www.wales247.co.uk/ai-model-predicts-injury-risk-in-rugby-union |
| Persons | Julian Owen, Seren Evans |
| Title | AI Model Predicts Injury Risk in Rugby Union |
|---|---|
| Degree of recognition | National |
| Media name/outlet | Business News Wales |
| Media type | Web |
| Country/Territory | United Kingdom |
| Date | 17/12/24 |
| Description | The first AI model that can predict the risk of non-contact lower limb injury in rugby players has been developed by researchers at Bangor University. The model uses pattern recognition analysis to identify the complex and interconnected factors that can lead to injuries such as sprained ankles, torn or sprained ligaments and more severe muscle strains. Lower limb injuries are the most common type in rugby union, accounting for about half of the days lost due to injury in the international game. The researchers, from Bangor University’s Rugby Knowledge Exchange followed 36 semi-professional rugby union players throughout two seasons, using data on training load, performance testing, subjective measures, musculoskeletal screening and prior injuries. More than 1700 data points were gathered for each player per playing season. |
| URL | https://businessnewswales.com/ai-model-predicts-injury-risk-in-rugby-union/ |
| Persons | Julian Owen, Seren Evans |