Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention

<p dir="ltr">Artificial Intelligence (AI) has gained huge attention in computer-aided decision-making in the healthcare domain. Many novel AI methods have been developed for disease diagnosis and prognosis which may support in the prevention of disease. Most diseases can be cured ear...

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Main Author: Hazrat Ali (421019) (author)
Other Authors: Zubair Shah (231886) (author), Tanvir Alam (638619) (author), Priyantha Wijayatunga (3446435) (author), Eyad Elyan (17296126) (author)
Published: 2024
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author Hazrat Ali (421019)
author2 Zubair Shah (231886)
Tanvir Alam (638619)
Priyantha Wijayatunga (3446435)
Eyad Elyan (17296126)
author2_role author
author
author
author
author_facet Hazrat Ali (421019)
Zubair Shah (231886)
Tanvir Alam (638619)
Priyantha Wijayatunga (3446435)
Eyad Elyan (17296126)
author_role author
dc.creator.none.fl_str_mv Hazrat Ali (421019)
Zubair Shah (231886)
Tanvir Alam (638619)
Priyantha Wijayatunga (3446435)
Eyad Elyan (17296126)
dc.date.none.fl_str_mv 2024-01-10T09:00:00Z
dc.identifier.none.fl_str_mv 10.3389/fradi.2023.1349830
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Editorial_Recent_advances_in_multimodal_artificial_intelligence_for_disease_diagnosis_prognosis_and_prevention/26389450
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
Information and computing sciences
Artificial intelligence
electronic health records
healthcare
medical imaging
radiology
multimodal artificial intelligence
vision transformers
dc.title.none.fl_str_mv Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
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) has gained huge attention in computer-aided decision-making in the healthcare domain. Many novel AI methods have been developed for disease diagnosis and prognosis which may support in the prevention of disease. Most diseases can be cured early and managed better if timely diagnosis is made. The AI models can aid clinical diagnosis; thus, they make the processes more efficient by reducing the workload of physicians, nurses, radiologists, and others. However, the majority of AI methods rely on the use of single-modality data.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Radiology<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/10.3389/fradi.2023.1349830" target="_blank">https://dx.doi.org/10.3389/fradi.2023.1349830</a></p>
eu_rights_str_mv openAccess
id Manara2_31ce90397447ae3d5fd9de8eb4df3871
identifier_str_mv 10.3389/fradi.2023.1349830
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/26389450
publishDate 2024
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rights_invalid_str_mv CC BY 4.0
spelling Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and preventionHazrat Ali (421019)Zubair Shah (231886)Tanvir Alam (638619)Priyantha Wijayatunga (3446435)Eyad Elyan (17296126)Health sciencesHealth services and systemsInformation and computing sciencesArtificial intelligenceelectronic health recordshealthcaremedical imagingradiologymultimodal artificial intelligencevision transformers<p dir="ltr">Artificial Intelligence (AI) has gained huge attention in computer-aided decision-making in the healthcare domain. Many novel AI methods have been developed for disease diagnosis and prognosis which may support in the prevention of disease. Most diseases can be cured early and managed better if timely diagnosis is made. The AI models can aid clinical diagnosis; thus, they make the processes more efficient by reducing the workload of physicians, nurses, radiologists, and others. However, the majority of AI methods rely on the use of single-modality data.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Radiology<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/10.3389/fradi.2023.1349830" target="_blank">https://dx.doi.org/10.3389/fradi.2023.1349830</a></p>2024-01-10T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/fradi.2023.1349830https://figshare.com/articles/journal_contribution/Editorial_Recent_advances_in_multimodal_artificial_intelligence_for_disease_diagnosis_prognosis_and_prevention/26389450CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/263894502024-01-10T09:00:00Z
spellingShingle Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
Hazrat Ali (421019)
Health sciences
Health services and systems
Information and computing sciences
Artificial intelligence
electronic health records
healthcare
medical imaging
radiology
multimodal artificial intelligence
vision transformers
status_str publishedVersion
title Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
title_full Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
title_fullStr Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
title_full_unstemmed Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
title_short Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
title_sort Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
topic Health sciences
Health services and systems
Information and computing sciences
Artificial intelligence
electronic health records
healthcare
medical imaging
radiology
multimodal artificial intelligence
vision transformers