A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects
<h3>Background</h3><p dir="ltr">Machine learning (ML) and deep learning (DL) methods have recently garnered a great deal of attention in the field of cancer research by making a noticeable contribution to the growth of predictive medicine and modern oncological practices....
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2022
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| _version_ | 1864513518573715456 |
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| author | Yousra El Alaoui (18427914) |
| author2 | Adel Elomri (8984063) Marwa Qaraqe (10135172) Regina Padmanabhan (14231606) Ruba Yasin Taha (18427917) Halima El Omri (14778790) Abdelfatteh EL Omri (18427920) Omar Aboumarzouk (18427923) |
| author2_role | author author author author author author author |
| author_facet | Yousra El Alaoui (18427914) Adel Elomri (8984063) Marwa Qaraqe (10135172) Regina Padmanabhan (14231606) Ruba Yasin Taha (18427917) Halima El Omri (14778790) Abdelfatteh EL Omri (18427920) Omar Aboumarzouk (18427923) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yousra El Alaoui (18427914) Adel Elomri (8984063) Marwa Qaraqe (10135172) Regina Padmanabhan (14231606) Ruba Yasin Taha (18427917) Halima El Omri (14778790) Abdelfatteh EL Omri (18427920) Omar Aboumarzouk (18427923) |
| dc.date.none.fl_str_mv | 2022-07-12T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.2196/36490 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_Review_of_Artificial_Intelligence_Applications_in_Hematology_Management_Current_Practices_and_Future_Prospects/25672521 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Health services and systems cancer oncology hematology machine learning deep learning artificial intelligence prediction malignancy management |
| dc.title.none.fl_str_mv | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Background</h3><p dir="ltr">Machine learning (ML) and deep learning (DL) methods have recently garnered a great deal of attention in the field of cancer research by making a noticeable contribution to the growth of predictive medicine and modern oncological practices. Considerable focus has been particularly directed toward hematologic malignancies because of the complexity in detecting early symptoms. Many patients with blood cancer do not get properly diagnosed until their cancer has reached an advanced stage with limited treatment prospects. Hence, the state-of-the-art revolves around the latest artificial intelligence (AI) applications in hematology management.</p><h3>Objective</h3><p dir="ltr">This comprehensive review provides an in-depth analysis of the current AI practices in the field of hematology. Our objective is to explore the ML and DL applications in blood cancer research, with a special focus on the type of hematologic malignancies and the patient’s cancer stage to determine future research directions in blood cancer.</p><h3>Methods</h3><p dir="ltr">We searched a set of recognized databases (Scopus, Springer, and Web of Science) using a selected number of keywords. We included studies written in English and published between 2015 and 2021. For each study, we identified the ML and DL techniques used and highlighted the performance of each model.</p><h3>Results</h3><p dir="ltr">Using the aforementioned inclusion criteria, the search resulted in 567 papers, of which 144 were selected for review.</p><h3>Conclusions</h3><p dir="ltr">The current literature suggests that the application of AI in the field of hematology has generated impressive results in the screening, diagnosis, and treatment stages. Nevertheless, optimizing the patient’s pathway to treatment requires a prior prediction of the malignancy based on the patient’s symptoms or blood records, which is an area that has still not been properly investigated.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Medical Internet Research<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.2196/36490" target="_blank">https://dx.doi.org/10.2196/36490</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_1aae21a25199c1ab6595066aad1eb3d0 |
| identifier_str_mv | 10.2196/36490 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25672521 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future ProspectsYousra El Alaoui (18427914)Adel Elomri (8984063)Marwa Qaraqe (10135172)Regina Padmanabhan (14231606)Ruba Yasin Taha (18427917)Halima El Omri (14778790)Abdelfatteh EL Omri (18427920)Omar Aboumarzouk (18427923)Health sciencesHealth services and systemscanceroncologyhematologymachine learningdeep learningartificial intelligencepredictionmalignancymanagement<h3>Background</h3><p dir="ltr">Machine learning (ML) and deep learning (DL) methods have recently garnered a great deal of attention in the field of cancer research by making a noticeable contribution to the growth of predictive medicine and modern oncological practices. Considerable focus has been particularly directed toward hematologic malignancies because of the complexity in detecting early symptoms. Many patients with blood cancer do not get properly diagnosed until their cancer has reached an advanced stage with limited treatment prospects. Hence, the state-of-the-art revolves around the latest artificial intelligence (AI) applications in hematology management.</p><h3>Objective</h3><p dir="ltr">This comprehensive review provides an in-depth analysis of the current AI practices in the field of hematology. Our objective is to explore the ML and DL applications in blood cancer research, with a special focus on the type of hematologic malignancies and the patient’s cancer stage to determine future research directions in blood cancer.</p><h3>Methods</h3><p dir="ltr">We searched a set of recognized databases (Scopus, Springer, and Web of Science) using a selected number of keywords. We included studies written in English and published between 2015 and 2021. For each study, we identified the ML and DL techniques used and highlighted the performance of each model.</p><h3>Results</h3><p dir="ltr">Using the aforementioned inclusion criteria, the search resulted in 567 papers, of which 144 were selected for review.</p><h3>Conclusions</h3><p dir="ltr">The current literature suggests that the application of AI in the field of hematology has generated impressive results in the screening, diagnosis, and treatment stages. Nevertheless, optimizing the patient’s pathway to treatment requires a prior prediction of the malignancy based on the patient’s symptoms or blood records, which is an area that has still not been properly investigated.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Medical Internet Research<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.2196/36490" target="_blank">https://dx.doi.org/10.2196/36490</a></p>2022-07-12T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.2196/36490https://figshare.com/articles/journal_contribution/A_Review_of_Artificial_Intelligence_Applications_in_Hematology_Management_Current_Practices_and_Future_Prospects/25672521CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/256725212022-07-12T03:00:00Z |
| spellingShingle | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects Yousra El Alaoui (18427914) Health sciences Health services and systems cancer oncology hematology machine learning deep learning artificial intelligence prediction malignancy management |
| status_str | publishedVersion |
| title | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| title_full | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| title_fullStr | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| title_full_unstemmed | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| title_short | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| title_sort | A Review of Artificial Intelligence Applications in Hematology Management: Current Practices and Future Prospects |
| topic | Health sciences Health services and systems cancer oncology hematology machine learning deep learning artificial intelligence prediction malignancy management |