Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review
Utilizing information from multiple sources is a preferred and more precise method for medical experts to confirm a diagnosis. Each source provides critical information about the disease that might otherwise be absent in other modalities. Combining information from various medical sources boosts con...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/11/12/1233 |
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| author | Sachin Kumar Sita Rani Shivani Sharma Hong Min |
| author_facet | Sachin Kumar Sita Rani Shivani Sharma Hong Min |
| author_sort | Sachin Kumar |
| collection | DOAJ |
| description | Utilizing information from multiple sources is a preferred and more precise method for medical experts to confirm a diagnosis. Each source provides critical information about the disease that might otherwise be absent in other modalities. Combining information from various medical sources boosts confidence in the diagnosis process, enabling the creation of an effective treatment plan for the patient. The scarcity of medical experts to diagnose diseases motivates the development of automatic diagnoses relying on multimodal data. With the progress in artificial intelligence technology, automated diagnosis using multimodal fusion techniques is now possible. Nevertheless, the concept of multimodal medical diagnosis is still new and requires an understanding of the diverse aspects of multimodal data and its related challenges. This review article examines the various aspects of multimodal medical diagnosis to equip readers, academicians, and researchers with necessary knowledge to advance multimodal medical research. The chosen articles in the study underwent thorough screening from reputable journals and publishers to offer high-quality content to readers, who can then apply the knowledge to produce quality research. Besides, the need for multimodal information and the associated challenges are discussed with solutions. Additionally, ethical issues of using artificial intelligence in medical diagnosis is also discussed. |
| format | Article |
| id | doaj-art-dd2ca4fc926546e88f91b84b0c5b5872 |
| institution | Kabale University |
| issn | 2306-5354 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj-art-dd2ca4fc926546e88f91b84b0c5b58722024-12-27T14:11:34ZengMDPI AGBioengineering2306-53542024-12-011112123310.3390/bioengineering11121233Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive ReviewSachin Kumar0Sita Rani1Shivani Sharma2Hong Min3Akian College of Science and Engineering, American University of Armenia, Yerevan 0019, ArmeniaDepartment of Computer Science and Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, IndiaDepartment of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala 147004, IndiaSchool of Computing, Gachon University, Seongnam 13120, Republic of KoreaUtilizing information from multiple sources is a preferred and more precise method for medical experts to confirm a diagnosis. Each source provides critical information about the disease that might otherwise be absent in other modalities. Combining information from various medical sources boosts confidence in the diagnosis process, enabling the creation of an effective treatment plan for the patient. The scarcity of medical experts to diagnose diseases motivates the development of automatic diagnoses relying on multimodal data. With the progress in artificial intelligence technology, automated diagnosis using multimodal fusion techniques is now possible. Nevertheless, the concept of multimodal medical diagnosis is still new and requires an understanding of the diverse aspects of multimodal data and its related challenges. This review article examines the various aspects of multimodal medical diagnosis to equip readers, academicians, and researchers with necessary knowledge to advance multimodal medical research. The chosen articles in the study underwent thorough screening from reputable journals and publishers to offer high-quality content to readers, who can then apply the knowledge to produce quality research. Besides, the need for multimodal information and the associated challenges are discussed with solutions. Additionally, ethical issues of using artificial intelligence in medical diagnosis is also discussed.https://www.mdpi.com/2306-5354/11/12/1233multimodal diagnosismultimodal fusionmultimodal challenges |
| spellingShingle | Sachin Kumar Sita Rani Shivani Sharma Hong Min Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review Bioengineering multimodal diagnosis multimodal fusion multimodal challenges |
| title | Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review |
| title_full | Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review |
| title_fullStr | Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review |
| title_full_unstemmed | Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review |
| title_short | Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review |
| title_sort | multimodality fusion aspects of medical diagnosis a comprehensive review |
| topic | multimodal diagnosis multimodal fusion multimodal challenges |
| url | https://www.mdpi.com/2306-5354/11/12/1233 |
| work_keys_str_mv | AT sachinkumar multimodalityfusionaspectsofmedicaldiagnosisacomprehensivereview AT sitarani multimodalityfusionaspectsofmedicaldiagnosisacomprehensivereview AT shivanisharma multimodalityfusionaspectsofmedicaldiagnosisacomprehensivereview AT hongmin multimodalityfusionaspectsofmedicaldiagnosisacomprehensivereview |