Using artificial intelligence to improve body iron quantification: A scoping review
<p dir="ltr">This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies that utilize machine learning in iron-related...
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2023
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| _version_ | 1864513539483369472 |
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| author | Abdulqadir J. Nashwan (11659453) |
| author2 | Ibraheem M. Alkhawaldeh (17430888) Nour Shaheen (14034758) Ibrahem Albalkhi (17430891) Ibrahim Serag (17430894) Khalid Sarhan (17430897) Ahmad A. Abujaber (14586054) Alaa Abd-Alrazaq (17430900) Mohamed A. Yassin (8361183) |
| author2_role | author author author author author author author author |
| author_facet | Abdulqadir J. Nashwan (11659453) Ibraheem M. Alkhawaldeh (17430888) Nour Shaheen (14034758) Ibrahem Albalkhi (17430891) Ibrahim Serag (17430894) Khalid Sarhan (17430897) Ahmad A. Abujaber (14586054) Alaa Abd-Alrazaq (17430900) Mohamed A. Yassin (8361183) |
| author_role | author |
| dc.creator.none.fl_str_mv | Abdulqadir J. Nashwan (11659453) Ibraheem M. Alkhawaldeh (17430888) Nour Shaheen (14034758) Ibrahem Albalkhi (17430891) Ibrahim Serag (17430894) Khalid Sarhan (17430897) Ahmad A. Abujaber (14586054) Alaa Abd-Alrazaq (17430900) Mohamed A. Yassin (8361183) |
| dc.date.none.fl_str_mv | 2023-09-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.blre.2023.101133 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/preprint/Using_artificial_intelligence_to_improve_body_iron_quantification_A_scoping_review/24607086 |
| 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 Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Iron overload Machine learning Liver Iron concentration Deep learning Hemochromatosis Anemia |
| dc.title.none.fl_str_mv | Using artificial intelligence to improve body iron quantification: A scoping review |
| dc.type.none.fl_str_mv | Text Preprint info:eu-repo/semantics/publishedVersion text preprint |
| description | <p dir="ltr">This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies that utilize machine learning in iron-related disorders. The search revealed a wide range of machine learning algorithms used by different studies. Notably, most studies used a single data type. The studies varied in terms of sample sizes, participant ages, and geographical locations. AI's role in quantifying iron concentration is still in its early stages, yet its potential is significant. The question is whether AI-based diagnostic biomarkers can offer innovative approaches for screening, diagnosing, and monitoring of iron overload and anemia.</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="https://dx.doi.org/10.1016/j.blre.2023.101133" target="_blank">https://dx.doi.org/10.1016/j.blre.2023.101133</a></p><p dir="ltr">Additional institutions affiliated with: Artificial Intelligence (AI) Center for Precision Health - WCM-Q</p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_51a38746629d0f91c5ab4466844f17c0 |
| identifier_str_mv | 10.1016/j.blre.2023.101133 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24607086 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Using artificial intelligence to improve body iron quantification: A scoping reviewAbdulqadir J. Nashwan (11659453)Ibraheem M. Alkhawaldeh (17430888)Nour Shaheen (14034758)Ibrahem Albalkhi (17430891)Ibrahim Serag (17430894)Khalid Sarhan (17430897)Ahmad A. Abujaber (14586054)Alaa Abd-Alrazaq (17430900)Mohamed A. Yassin (8361183)Biomedical and clinical sciencesCardiovascular medicine and haematologyInformation and computing sciencesArtificial intelligenceMachine learningArtificial intelligenceIron overloadMachine learningLiver Iron concentrationDeep learningHemochromatosisAnemia<p dir="ltr">This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies that utilize machine learning in iron-related disorders. The search revealed a wide range of machine learning algorithms used by different studies. Notably, most studies used a single data type. The studies varied in terms of sample sizes, participant ages, and geographical locations. AI's role in quantifying iron concentration is still in its early stages, yet its potential is significant. The question is whether AI-based diagnostic biomarkers can offer innovative approaches for screening, diagnosing, and monitoring of iron overload and anemia.</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="https://dx.doi.org/10.1016/j.blre.2023.101133" target="_blank">https://dx.doi.org/10.1016/j.blre.2023.101133</a></p><p dir="ltr">Additional institutions affiliated with: Artificial Intelligence (AI) Center for Precision Health - WCM-Q</p>2023-09-01T00:00:00ZTextPreprintinfo:eu-repo/semantics/publishedVersiontextpreprint10.1016/j.blre.2023.101133https://figshare.com/articles/preprint/Using_artificial_intelligence_to_improve_body_iron_quantification_A_scoping_review/24607086CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/246070862023-09-01T00:00:00Z |
| spellingShingle | Using artificial intelligence to improve body iron quantification: A scoping review Abdulqadir J. Nashwan (11659453) Biomedical and clinical sciences Cardiovascular medicine and haematology Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Iron overload Machine learning Liver Iron concentration Deep learning Hemochromatosis Anemia |
| status_str | publishedVersion |
| title | Using artificial intelligence to improve body iron quantification: A scoping review |
| title_full | Using artificial intelligence to improve body iron quantification: A scoping review |
| title_fullStr | Using artificial intelligence to improve body iron quantification: A scoping review |
| title_full_unstemmed | Using artificial intelligence to improve body iron quantification: A scoping review |
| title_short | Using artificial intelligence to improve body iron quantification: A scoping review |
| title_sort | Using artificial intelligence to improve body iron quantification: A scoping review |
| topic | Biomedical and clinical sciences Cardiovascular medicine and haematology Information and computing sciences Artificial intelligence Machine learning Artificial intelligence Iron overload Machine learning Liver Iron concentration Deep learning Hemochromatosis Anemia |