Artificial intelligence in sickle disease
<p dir="ltr">Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, inc...
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| مؤلفون آخرون: | , , , , , , , , , , , |
| منشور في: |
2023
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| _version_ | 1864513558690136064 |
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| author | Ahmed Elsabagh (15455321) |
| author2 | Mohamed Elhadary (16329082) Basel Elsayed (14614273) Amgad Mohamed Elshoeibi (16329083) Khaled Ferih (16329085) Rasha Kaddoura (12506936) Salam Alkindi (11601856) Awni Alshurafa (15468195) Mona Alrasheed (16329089) Abdullah Alzayed (8063072) Abdulrahman Al-Abdulmalek (16329091) Jaffer Abduljabber Altooq (16329092) Mohamed Yassin (4166515) |
| author2_role | author author author author author author author author author author author author |
| author_facet | Ahmed Elsabagh (15455321) Mohamed Elhadary (16329082) Basel Elsayed (14614273) Amgad Mohamed Elshoeibi (16329083) Khaled Ferih (16329085) Rasha Kaddoura (12506936) Salam Alkindi (11601856) Awni Alshurafa (15468195) Mona Alrasheed (16329089) Abdullah Alzayed (8063072) Abdulrahman Al-Abdulmalek (16329091) Jaffer Abduljabber Altooq (16329092) Mohamed Yassin (4166515) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ahmed Elsabagh (15455321) Mohamed Elhadary (16329082) Basel Elsayed (14614273) Amgad Mohamed Elshoeibi (16329083) Khaled Ferih (16329085) Rasha Kaddoura (12506936) Salam Alkindi (11601856) Awni Alshurafa (15468195) Mona Alrasheed (16329089) Abdullah Alzayed (8063072) Abdulrahman Al-Abdulmalek (16329091) Jaffer Abduljabber Altooq (16329092) Mohamed Yassin (4166515) |
| dc.date.none.fl_str_mv | 2023-09-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.blre.2023.101102 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Artificial_intelligence_in_sickle_disease/23514747 |
| 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 Oncology and carcinogenesis Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Sickle cell Machine learning Convolutional neural networks Hemoglobinopathies |
| dc.title.none.fl_str_mv | Artificial intelligence in sickle disease |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. <b>Aim</b>: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.</p><h2>Other Information</h2><p dir="ltr">Published in: Blood Reviews<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="http://dx.doi.org/10.1016/j.blre.2023.101102" target="_blank">http://dx.doi.org/10.1016/j.blre.2023.101102</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_3d9d3846b5e47ebabcb9e1603b500464 |
| identifier_str_mv | 10.1016/j.blre.2023.101102 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/23514747 |
| publishDate | 2023 |
| 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 sickle diseaseAhmed Elsabagh (15455321)Mohamed Elhadary (16329082)Basel Elsayed (14614273)Amgad Mohamed Elshoeibi (16329083)Khaled Ferih (16329085)Rasha Kaddoura (12506936)Salam Alkindi (11601856)Awni Alshurafa (15468195)Mona Alrasheed (16329089)Abdullah Alzayed (8063072)Abdulrahman Al-Abdulmalek (16329091)Jaffer Abduljabber Altooq (16329092)Mohamed Yassin (4166515)Biomedical and clinical sciencesCardiovascular medicine and haematologyOncology and carcinogenesisInformation and computing sciencesArtificial intelligenceMachine learningArtificial intelligenceSickle cellMachine learningConvolutional neural networksHemoglobinopathies<p dir="ltr">Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. <b>Aim</b>: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.</p><h2>Other Information</h2><p dir="ltr">Published in: Blood Reviews<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="http://dx.doi.org/10.1016/j.blre.2023.101102" target="_blank">http://dx.doi.org/10.1016/j.blre.2023.101102</a></p>2023-09-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.blre.2023.101102https://figshare.com/articles/journal_contribution/Artificial_intelligence_in_sickle_disease/23514747CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/235147472023-09-01T00:00:00Z |
| spellingShingle | Artificial intelligence in sickle disease Ahmed Elsabagh (15455321) Biomedical and clinical sciences Cardiovascular medicine and haematology Oncology and carcinogenesis Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Sickle cell Machine learning Convolutional neural networks Hemoglobinopathies |
| status_str | publishedVersion |
| title | Artificial intelligence in sickle disease |
| title_full | Artificial intelligence in sickle disease |
| title_fullStr | Artificial intelligence in sickle disease |
| title_full_unstemmed | Artificial intelligence in sickle disease |
| title_short | Artificial intelligence in sickle disease |
| title_sort | Artificial intelligence in sickle disease |
| topic | Biomedical and clinical sciences Cardiovascular medicine and haematology Oncology and carcinogenesis Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Sickle cell Machine learning Convolutional neural networks Hemoglobinopathies |