Artificial Intelligence in Enhancing Syncope Management - An Update
<p dir="ltr">This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratificati...
محفوظ في:
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2024
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إضافة وسم
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| _version_ | 1864513549504610304 |
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| author | Alifiya Aamir (17032323) |
| author2 | Yumna Jamil (17032326) Maham Bilal (17032329) Mufaddal Diwan (17032332) Abdulqadir J. Nashwan (14586036) Irfan Ullah (847820) |
| author2_role | author author author author author |
| author_facet | Alifiya Aamir (17032323) Yumna Jamil (17032326) Maham Bilal (17032329) Mufaddal Diwan (17032332) Abdulqadir J. Nashwan (14586036) Irfan Ullah (847820) |
| author_role | author |
| dc.creator.none.fl_str_mv | Alifiya Aamir (17032323) Yumna Jamil (17032326) Maham Bilal (17032329) Mufaddal Diwan (17032332) Abdulqadir J. Nashwan (14586036) Irfan Ullah (847820) |
| dc.date.none.fl_str_mv | 2024-01-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.cpcardiol.2023.102079 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Artificial_Intelligence_in_Enhancing_Syncope_Management_-_An_Update/24419815 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Cardiovascular medicine and haematology Clinical sciences Education Specialist studies in education Health sciences Health services and systems Information and computing sciences Artificial intelligence Loss of consciousness Cerebral hypoperfusion Patient management Artificial Intelligence Clinical decision support tools |
| dc.title.none.fl_str_mv | Artificial Intelligence in Enhancing Syncope Management - An Update |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratification, syncope poses significant healthcare challenges. AI has the potential to improve symptom differentiation, risk assessment, and patient management. Machine learning, specifically Artificial Neural Networks, has shown promise in accurate risk stratification. AI-powered clinical decision support tools can improve patient evaluation and resource utilization. While AI holds great promise for syncope management, challenges such as data quality, class imbalance, and defining risk categories remain. Ethical concerns about patient privacy, as well as the need for human empathy, complicate AI integration. Collaboration among data scientists, clinicians, and ethics experts is critical for the successful implementation of AI, which has the potential to improve patient outcomes and healthcare efficiency in syncope management.</p><h2>Other Information</h2><p dir="ltr">Published in: Current Problems in Cardiology<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://doi.org/10.1016/j.cpcardiol.2023.102079" rel="noreferrer" target="_blank">https://doi.org/10.1016/j.cpcardiol.2023.102079</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_50f6f8815989cdd3a66971a3fc28d93c |
| identifier_str_mv | 10.1016/j.cpcardiol.2023.102079 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24419815 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Artificial Intelligence in Enhancing Syncope Management - An UpdateAlifiya Aamir (17032323)Yumna Jamil (17032326)Maham Bilal (17032329)Mufaddal Diwan (17032332)Abdulqadir J. Nashwan (14586036)Irfan Ullah (847820)Biomedical and clinical sciencesCardiovascular medicine and haematologyClinical sciencesEducationSpecialist studies in educationHealth sciencesHealth services and systemsInformation and computing sciencesArtificial intelligenceLoss of consciousnessCerebral hypoperfusionPatient managementArtificial IntelligenceClinical decision support tools<p dir="ltr">This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratification, syncope poses significant healthcare challenges. AI has the potential to improve symptom differentiation, risk assessment, and patient management. Machine learning, specifically Artificial Neural Networks, has shown promise in accurate risk stratification. AI-powered clinical decision support tools can improve patient evaluation and resource utilization. While AI holds great promise for syncope management, challenges such as data quality, class imbalance, and defining risk categories remain. Ethical concerns about patient privacy, as well as the need for human empathy, complicate AI integration. Collaboration among data scientists, clinicians, and ethics experts is critical for the successful implementation of AI, which has the potential to improve patient outcomes and healthcare efficiency in syncope management.</p><h2>Other Information</h2><p dir="ltr">Published in: Current Problems in Cardiology<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://doi.org/10.1016/j.cpcardiol.2023.102079" rel="noreferrer" target="_blank">https://doi.org/10.1016/j.cpcardiol.2023.102079</a></p>2024-01-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.cpcardiol.2023.102079https://figshare.com/articles/journal_contribution/Artificial_Intelligence_in_Enhancing_Syncope_Management_-_An_Update/24419815CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/244198152024-01-01T00:00:00Z |
| spellingShingle | Artificial Intelligence in Enhancing Syncope Management - An Update Alifiya Aamir (17032323) Biomedical and clinical sciences Cardiovascular medicine and haematology Clinical sciences Education Specialist studies in education Health sciences Health services and systems Information and computing sciences Artificial intelligence Loss of consciousness Cerebral hypoperfusion Patient management Artificial Intelligence Clinical decision support tools |
| status_str | publishedVersion |
| title | Artificial Intelligence in Enhancing Syncope Management - An Update |
| title_full | Artificial Intelligence in Enhancing Syncope Management - An Update |
| title_fullStr | Artificial Intelligence in Enhancing Syncope Management - An Update |
| title_full_unstemmed | Artificial Intelligence in Enhancing Syncope Management - An Update |
| title_short | Artificial Intelligence in Enhancing Syncope Management - An Update |
| title_sort | Artificial Intelligence in Enhancing Syncope Management - An Update |
| topic | Biomedical and clinical sciences Cardiovascular medicine and haematology Clinical sciences Education Specialist studies in education Health sciences Health services and systems Information and computing sciences Artificial intelligence Loss of consciousness Cerebral hypoperfusion Patient management Artificial Intelligence Clinical decision support tools |