Artificial Intelligence in Predicting Heart Failure
| Author | Al-Mannai, Rashid Ebrahim |
| Author | Almerekhi, Mohammed Hamad |
| Author | Al-Mannai, Mohammed Abdulla |
| Author | N, Mishahira |
| Author | Sadasivuni, Kishor Kumar |
| Author | Yalcin, Huseyin Cagatay |
| Author | Ouakad, Hassen M. |
| Author | Bahadur, Issam |
| Author | Al-Maadeed, Somaya |
| Author | Albusaidi, Asiya |
| Available date | 2021-10-18T08:15:40Z |
| Publication Date | 2021 |
| Publication Name | Qatar University Annual Research an Exhibition 2021 (quarfe) |
| Citation | Al-Mannai R. E., Almerekhi M. H., Al-Mannai M. A., Shahira N., Sadasivuni K. K., Yalcin H. C., Ouakad H. M., Bahadur I., Al-Maadeed S., Albusaidi A., "ARTIFICIAL INTELLIGENCE IN PREDICTING HEART FAILURE", Qatar University Annual Research Forum and Exhibition (QUARFE 2021), Doha, 20 October 2021, https://doi.org/10.29117/quarfe.2021.0130 |
| Abstract | Heart Failure is a major chronic disease that is increasing day by day and a great health burden in health care systems world wide. Artificial intelligence (AI) techniques such as machine learning (ML), deep learning (DL), and cognitive computer can play a critical role in the early detection and diagnosis of Heart Failure Detection, as well as outcome prediction and prognosis evaluation. The availability of large datasets from difference sources can be leveraged to build machine learning models that can empower clinicians by providing early warnings and insightful information on the underlying conditions of the patients |
| Language | en |
| Publisher | Qatar University Press |
| Subject | Artificial intelligence Machine learning Heart failure Matlab |
| Type | Poster |
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