Federated Learning for Multi-Modal Health Data Integration: Enhancing Diagnostic Accuracy and Ensuring Data Privacy Article Swipe
The healthcare sector is experiencing a surge in diverse health data, encompassing medical imaging, electronic health records and live sensor readings from wearable technology. Integrating these multi-modal datasets holds immense potential for improving medical care by facilitating better diagnostic accuracy, customized therapeutic approaches, and more comprehensive understanding of how diseases evolve. However, centralizing this sensitive patient data across various institutions raises significant privacy concerns and raises complex issues around data stewardship and administrative oversight.Federated learning has surfaced as a potential approach to harness the wealth of available data while safeguarding patient privacy. Federated Learning (FL) facilitates a collaborative approach to model training among various healthcare institutions, allowing them to work together without needing to exchange their raw data. This research presents an innovative FL framework specifically designed to integrate multi-modal health data. Our method tackles the issues of data variability and model integration in federated environments, with the goal of improving diagnostic precision and personalizing treatment suggestions, all while maintaining the confidentiality of patient data.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.22214/ijraset.2025.66865
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407342299
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4407342299Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.22214/ijraset.2025.66865Digital Object Identifier
- Title
-
Federated Learning for Multi-Modal Health Data Integration: Enhancing Diagnostic Accuracy and Ensuring Data PrivacyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-02-10Full publication date if available
- Authors
-
Arjun NairList of authors in order
- Landing page
-
https://doi.org/10.22214/ijraset.2025.66865Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.22214/ijraset.2025.66865Direct OA link when available
- Concepts
-
Modal, Computer science, Information privacy, Federated learning, Data integration, Health data, Internet privacy, Data science, Data mining, Artificial intelligence, Health care, Political science, Law, Chemistry, Polymer chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4407342299 |
|---|---|
| doi | https://doi.org/10.22214/ijraset.2025.66865 |
| ids.doi | https://doi.org/10.22214/ijraset.2025.66865 |
| ids.openalex | https://openalex.org/W4407342299 |
| fwci | 0.0 |
| type | article |
| title | Federated Learning for Multi-Modal Health Data Integration: Enhancing Diagnostic Accuracy and Ensuring Data Privacy |
| biblio.issue | 2 |
| biblio.volume | 13 |
| biblio.last_page | 403 |
| biblio.first_page | 396 |
| topics[0].id | https://openalex.org/T10764 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9987000226974487 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Privacy-Preserving Technologies in Data |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C71139939 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7705711722373962 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q910194 |
| concepts[0].display_name | Modal |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6640043258666992 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C123201435 |
| concepts[2].level | 2 |
| concepts[2].score | 0.43553879857063293 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q456632 |
| concepts[2].display_name | Information privacy |
| concepts[3].id | https://openalex.org/C2992525071 |
| concepts[3].level | 2 |
| concepts[3].score | 0.43172502517700195 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q50818671 |
| concepts[3].display_name | Federated learning |
| concepts[4].id | https://openalex.org/C72634772 |
| concepts[4].level | 2 |
| concepts[4].score | 0.42174577713012695 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q386824 |
| concepts[4].display_name | Data integration |
| concepts[5].id | https://openalex.org/C3017977704 |
| concepts[5].level | 3 |
| concepts[5].score | 0.4185894727706909 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q18745135 |
| concepts[5].display_name | Health data |
| concepts[6].id | https://openalex.org/C108827166 |
| concepts[6].level | 1 |
| concepts[6].score | 0.391818106174469 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q175975 |
| concepts[6].display_name | Internet privacy |
| concepts[7].id | https://openalex.org/C2522767166 |
| concepts[7].level | 1 |
| concepts[7].score | 0.3813050389289856 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[7].display_name | Data science |
| concepts[8].id | https://openalex.org/C124101348 |
| concepts[8].level | 1 |
| concepts[8].score | 0.3506864905357361 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[8].display_name | Data mining |
| concepts[9].id | https://openalex.org/C154945302 |
| concepts[9].level | 1 |
| concepts[9].score | 0.26894837617874146 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[9].display_name | Artificial intelligence |
| concepts[10].id | https://openalex.org/C160735492 |
| concepts[10].level | 2 |
| concepts[10].score | 0.13523787260055542 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q31207 |
| concepts[10].display_name | Health care |
| concepts[11].id | https://openalex.org/C17744445 |
| concepts[11].level | 0 |
| concepts[11].score | 0.04966157674789429 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[11].display_name | Political science |
| concepts[12].id | https://openalex.org/C199539241 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[12].display_name | Law |
| concepts[13].id | https://openalex.org/C185592680 |
| concepts[13].level | 0 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[13].display_name | Chemistry |
| concepts[14].id | https://openalex.org/C188027245 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q750446 |
| concepts[14].display_name | Polymer chemistry |
| keywords[0].id | https://openalex.org/keywords/modal |
| keywords[0].score | 0.7705711722373962 |
| keywords[0].display_name | Modal |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6640043258666992 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/information-privacy |
| keywords[2].score | 0.43553879857063293 |
| keywords[2].display_name | Information privacy |
| keywords[3].id | https://openalex.org/keywords/federated-learning |
| keywords[3].score | 0.43172502517700195 |
| keywords[3].display_name | Federated learning |
| keywords[4].id | https://openalex.org/keywords/data-integration |
| keywords[4].score | 0.42174577713012695 |
| keywords[4].display_name | Data integration |
| keywords[5].id | https://openalex.org/keywords/health-data |
| keywords[5].score | 0.4185894727706909 |
| keywords[5].display_name | Health data |
| keywords[6].id | https://openalex.org/keywords/internet-privacy |
| keywords[6].score | 0.391818106174469 |
| keywords[6].display_name | Internet privacy |
| keywords[7].id | https://openalex.org/keywords/data-science |
| keywords[7].score | 0.3813050389289856 |
| keywords[7].display_name | Data science |
| keywords[8].id | https://openalex.org/keywords/data-mining |
| keywords[8].score | 0.3506864905357361 |
| keywords[8].display_name | Data mining |
| keywords[9].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[9].score | 0.26894837617874146 |
| keywords[9].display_name | Artificial intelligence |
| keywords[10].id | https://openalex.org/keywords/health-care |
| keywords[10].score | 0.13523787260055542 |
| keywords[10].display_name | Health care |
| keywords[11].id | https://openalex.org/keywords/political-science |
| keywords[11].score | 0.04966157674789429 |
| keywords[11].display_name | Political science |
| language | en |
| locations[0].id | doi:10.22214/ijraset.2025.66865 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764566388 |
| locations[0].source.issn | 2321-9653 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2321-9653 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | International Journal for Research in Applied Science and Engineering Technology |
| locations[0].source.host_organization | https://openalex.org/P4322614460 |
| locations[0].source.host_organization_name | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| locations[0].source.host_organization_lineage | https://openalex.org/P4322614460 |
| locations[0].source.host_organization_lineage_names | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | International Journal for Research in Applied Science and Engineering Technology |
| locations[0].landing_page_url | https://doi.org/10.22214/ijraset.2025.66865 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5077626501 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-9270-3771 |
| authorships[0].author.display_name | Arjun Nair |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Arjun Nair |
| authorships[0].is_corresponding | True |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.22214/ijraset.2025.66865 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Federated Learning for Multi-Modal Health Data Integration: Enhancing Diagnostic Accuracy and Ensuring Data Privacy |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10764 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9987000226974487 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Privacy-Preserving Technologies in Data |
| related_works | https://openalex.org/W4298221930, https://openalex.org/W2777914285, https://openalex.org/W4378677776, https://openalex.org/W3013363440, https://openalex.org/W4287823391, https://openalex.org/W2606756185, https://openalex.org/W4285279634, https://openalex.org/W2993649566, https://openalex.org/W3027570016, https://openalex.org/W3125775377 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.22214/ijraset.2025.66865 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764566388 |
| best_oa_location.source.issn | 2321-9653 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2321-9653 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | International Journal for Research in Applied Science and Engineering Technology |
| best_oa_location.source.host_organization | https://openalex.org/P4322614460 |
| best_oa_location.source.host_organization_name | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4322614460 |
| best_oa_location.source.host_organization_lineage_names | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| best_oa_location.license | |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | International Journal for Research in Applied Science and Engineering Technology |
| best_oa_location.landing_page_url | https://doi.org/10.22214/ijraset.2025.66865 |
| primary_location.id | doi:10.22214/ijraset.2025.66865 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764566388 |
| primary_location.source.issn | 2321-9653 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2321-9653 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | International Journal for Research in Applied Science and Engineering Technology |
| primary_location.source.host_organization | https://openalex.org/P4322614460 |
| primary_location.source.host_organization_name | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| primary_location.source.host_organization_lineage | https://openalex.org/P4322614460 |
| primary_location.source.host_organization_lineage_names | International Journal for Research in Applied Science and Engineering Technology (IJRASET) |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | International Journal for Research in Applied Science and Engineering Technology |
| primary_location.landing_page_url | https://doi.org/10.22214/ijraset.2025.66865 |
| publication_date | 2025-02-10 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 5, 78, 96 |
| abstract_inverted_index.FL | 123 |
| abstract_inverted_index.an | 121 |
| abstract_inverted_index.as | 77 |
| abstract_inverted_index.by | 35 |
| abstract_inverted_index.in | 7, 143 |
| abstract_inverted_index.is | 3 |
| abstract_inverted_index.of | 47, 85, 137, 149, 162 |
| abstract_inverted_index.to | 81, 99, 108, 113, 127 |
| abstract_inverted_index.Our | 132 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.all | 157 |
| abstract_inverted_index.and | 17, 43, 64, 71, 140, 153 |
| abstract_inverted_index.for | 31 |
| abstract_inverted_index.has | 75 |
| abstract_inverted_index.how | 48 |
| abstract_inverted_index.raw | 116 |
| abstract_inverted_index.the | 83, 135, 147, 160 |
| abstract_inverted_index.(FL) | 94 |
| abstract_inverted_index.This | 118 |
| abstract_inverted_index.care | 34 |
| abstract_inverted_index.data | 56, 69, 87, 138 |
| abstract_inverted_index.from | 21 |
| abstract_inverted_index.goal | 148 |
| abstract_inverted_index.live | 18 |
| abstract_inverted_index.more | 44 |
| abstract_inverted_index.them | 107 |
| abstract_inverted_index.this | 53 |
| abstract_inverted_index.with | 146 |
| abstract_inverted_index.work | 109 |
| abstract_inverted_index.among | 102 |
| abstract_inverted_index.data, | 10 |
| abstract_inverted_index.data. | 117, 131, 164 |
| abstract_inverted_index.holds | 28 |
| abstract_inverted_index.model | 100, 141 |
| abstract_inverted_index.surge | 6 |
| abstract_inverted_index.their | 115 |
| abstract_inverted_index.these | 25 |
| abstract_inverted_index.while | 88, 158 |
| abstract_inverted_index.across | 57 |
| abstract_inverted_index.around | 68 |
| abstract_inverted_index.better | 37 |
| abstract_inverted_index.health | 9, 15, 130 |
| abstract_inverted_index.issues | 67, 136 |
| abstract_inverted_index.method | 133 |
| abstract_inverted_index.raises | 60, 65 |
| abstract_inverted_index.sector | 2 |
| abstract_inverted_index.sensor | 19 |
| abstract_inverted_index.wealth | 84 |
| abstract_inverted_index.complex | 66 |
| abstract_inverted_index.diverse | 8 |
| abstract_inverted_index.evolve. | 50 |
| abstract_inverted_index.harness | 82 |
| abstract_inverted_index.immense | 29 |
| abstract_inverted_index.medical | 12, 33 |
| abstract_inverted_index.needing | 112 |
| abstract_inverted_index.patient | 55, 90, 163 |
| abstract_inverted_index.privacy | 62 |
| abstract_inverted_index.records | 16 |
| abstract_inverted_index.tackles | 134 |
| abstract_inverted_index.various | 58, 103 |
| abstract_inverted_index.without | 111 |
| abstract_inverted_index.However, | 51 |
| abstract_inverted_index.Learning | 93 |
| abstract_inverted_index.allowing | 106 |
| abstract_inverted_index.approach | 80, 98 |
| abstract_inverted_index.concerns | 63 |
| abstract_inverted_index.datasets | 27 |
| abstract_inverted_index.designed | 126 |
| abstract_inverted_index.diseases | 49 |
| abstract_inverted_index.exchange | 114 |
| abstract_inverted_index.imaging, | 13 |
| abstract_inverted_index.learning | 74 |
| abstract_inverted_index.presents | 120 |
| abstract_inverted_index.privacy. | 91 |
| abstract_inverted_index.readings | 20 |
| abstract_inverted_index.research | 119 |
| abstract_inverted_index.surfaced | 76 |
| abstract_inverted_index.together | 110 |
| abstract_inverted_index.training | 101 |
| abstract_inverted_index.wearable | 22 |
| abstract_inverted_index.Federated | 92 |
| abstract_inverted_index.accuracy, | 39 |
| abstract_inverted_index.available | 86 |
| abstract_inverted_index.federated | 144 |
| abstract_inverted_index.framework | 124 |
| abstract_inverted_index.improving | 32, 150 |
| abstract_inverted_index.integrate | 128 |
| abstract_inverted_index.potential | 30, 79 |
| abstract_inverted_index.precision | 152 |
| abstract_inverted_index.sensitive | 54 |
| abstract_inverted_index.treatment | 155 |
| abstract_inverted_index.customized | 40 |
| abstract_inverted_index.diagnostic | 38, 151 |
| abstract_inverted_index.electronic | 14 |
| abstract_inverted_index.healthcare | 1, 104 |
| abstract_inverted_index.innovative | 122 |
| abstract_inverted_index.Integrating | 24 |
| abstract_inverted_index.approaches, | 42 |
| abstract_inverted_index.facilitates | 95 |
| abstract_inverted_index.integration | 142 |
| abstract_inverted_index.maintaining | 159 |
| abstract_inverted_index.multi-modal | 26, 129 |
| abstract_inverted_index.significant | 61 |
| abstract_inverted_index.stewardship | 70 |
| abstract_inverted_index.technology. | 23 |
| abstract_inverted_index.therapeutic | 41 |
| abstract_inverted_index.variability | 139 |
| abstract_inverted_index.centralizing | 52 |
| abstract_inverted_index.encompassing | 11 |
| abstract_inverted_index.experiencing | 4 |
| abstract_inverted_index.facilitating | 36 |
| abstract_inverted_index.institutions | 59 |
| abstract_inverted_index.safeguarding | 89 |
| abstract_inverted_index.specifically | 125 |
| abstract_inverted_index.suggestions, | 156 |
| abstract_inverted_index.collaborative | 97 |
| abstract_inverted_index.comprehensive | 45 |
| abstract_inverted_index.environments, | 145 |
| abstract_inverted_index.institutions, | 105 |
| abstract_inverted_index.personalizing | 154 |
| abstract_inverted_index.understanding | 46 |
| abstract_inverted_index.administrative | 72 |
| abstract_inverted_index.confidentiality | 161 |
| abstract_inverted_index.oversight.Federated | 73 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5077626501 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| citation_normalized_percentile.value | 0.01430917 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |