Artificial Intelligence-Driven Translation Tool in Intensive Care Unit (AITIC) for Enhancing Communication and Research Article Swipe
Sahar Bahrami
,
Francesca Rubulotta
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202412.1686.v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202412.1686.v1
There is a need to improve communication for patients and family members who belong to cultural minority communities in the Intensive Care units (ICU). As a matter of fact, language barriers negatively impact patient safety, family participation in the care of the critically ill patients as well as recruitment in clinical trial. Recent studies indicate that Google translate and ChatGPT are not accurate enough for advanced medical terminology. Therefore, developing and implementing an Artificial Intelligence-driven language translation tool is essential for bridging language barriers. This tool will enable language minority communities to access advanced healthcare facilities and innovative research in a timely and effective manner, ensuring they receive the comprehensive care and information they need. Method: Key factors that facilitate access to advanced health services, in particular ICUs for language minority communities are reviewed. Results: The existing digital communication tools in emergency and the ICU are reviewed. To the best of our knowledge, no Al translation app has been developed for deployment in ICUs. Patient privacy and data confidentiality are other important issues that should be addressed. Conclusions: Developing AITC which uses language models trained with medical/ICU terminology dataset could offer fast and accurate real-time translation. AITIC could support communication, consolidate and expand original research involving language minority communities.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202412.1686.v1
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405715954
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4405715954Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.20944/preprints202412.1686.v1Digital Object Identifier
- Title
-
Artificial Intelligence-Driven Translation Tool in Intensive Care Unit (AITIC) for Enhancing Communication and ResearchWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-12-20Full publication date if available
- Authors
-
Sahar Bahrami, Francesca RubulottaList of authors in order
- Landing page
-
https://doi.org/10.20944/preprints202412.1686.v1Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.20944/preprints202412.1686.v1Direct OA link when available
- Concepts
-
Terminology, Software deployment, Health care, Bridging (networking), Confidentiality, Language barrier, Intensive care, Knowledge management, Computer science, Medicine, Nursing, Computer security, Political science, Intensive care medicine, Philosophy, Law, Linguistics, Operating systemTop 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/W4405715954 |
|---|---|
| doi | https://doi.org/10.20944/preprints202412.1686.v1 |
| ids.doi | https://doi.org/10.20944/preprints202412.1686.v1 |
| ids.openalex | https://openalex.org/W4405715954 |
| fwci | 0.0 |
| type | preprint |
| title | Artificial Intelligence-Driven Translation Tool in Intensive Care Unit (AITIC) for Enhancing Communication and Research |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11636 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9666000008583069 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2718 |
| topics[0].subfield.display_name | Health Informatics |
| topics[0].display_name | Artificial Intelligence in Healthcare and Education |
| topics[1].id | https://openalex.org/T10177 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9412999749183655 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2739 |
| topics[1].subfield.display_name | Public Health, Environmental and Occupational Health |
| topics[1].display_name | Palliative Care and End-of-Life Issues |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C547195049 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7517781257629395 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1725664 |
| concepts[0].display_name | Terminology |
| concepts[1].id | https://openalex.org/C105339364 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5701462030410767 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q2297740 |
| concepts[1].display_name | Software deployment |
| concepts[2].id | https://openalex.org/C160735492 |
| concepts[2].level | 2 |
| concepts[2].score | 0.522761344909668 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q31207 |
| concepts[2].display_name | Health care |
| concepts[3].id | https://openalex.org/C174348530 |
| concepts[3].level | 2 |
| concepts[3].score | 0.50565505027771 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q188635 |
| concepts[3].display_name | Bridging (networking) |
| concepts[4].id | https://openalex.org/C71745522 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4790978729724884 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2476929 |
| concepts[4].display_name | Confidentiality |
| concepts[5].id | https://openalex.org/C47602998 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4688645005226135 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2588869 |
| concepts[5].display_name | Language barrier |
| concepts[6].id | https://openalex.org/C2987404301 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4255700409412384 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q679690 |
| concepts[6].display_name | Intensive care |
| concepts[7].id | https://openalex.org/C56739046 |
| concepts[7].level | 1 |
| concepts[7].score | 0.4049435555934906 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q192060 |
| concepts[7].display_name | Knowledge management |
| concepts[8].id | https://openalex.org/C41008148 |
| concepts[8].level | 0 |
| concepts[8].score | 0.38704714179039 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[8].display_name | Computer science |
| concepts[9].id | https://openalex.org/C71924100 |
| concepts[9].level | 0 |
| concepts[9].score | 0.3651997447013855 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[9].display_name | Medicine |
| concepts[10].id | https://openalex.org/C159110408 |
| concepts[10].level | 1 |
| concepts[10].score | 0.320658415555954 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q121176 |
| concepts[10].display_name | Nursing |
| concepts[11].id | https://openalex.org/C38652104 |
| concepts[11].level | 1 |
| concepts[11].score | 0.18294724822044373 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q3510521 |
| concepts[11].display_name | Computer security |
| concepts[12].id | https://openalex.org/C17744445 |
| concepts[12].level | 0 |
| concepts[12].score | 0.10842785239219666 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[12].display_name | Political science |
| concepts[13].id | https://openalex.org/C177713679 |
| concepts[13].level | 1 |
| concepts[13].score | 0.10653647780418396 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q679690 |
| concepts[13].display_name | Intensive care medicine |
| concepts[14].id | https://openalex.org/C138885662 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[14].display_name | Philosophy |
| concepts[15].id | https://openalex.org/C199539241 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[15].display_name | Law |
| concepts[16].id | https://openalex.org/C41895202 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[16].display_name | Linguistics |
| concepts[17].id | https://openalex.org/C111919701 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[17].display_name | Operating system |
| keywords[0].id | https://openalex.org/keywords/terminology |
| keywords[0].score | 0.7517781257629395 |
| keywords[0].display_name | Terminology |
| keywords[1].id | https://openalex.org/keywords/software-deployment |
| keywords[1].score | 0.5701462030410767 |
| keywords[1].display_name | Software deployment |
| keywords[2].id | https://openalex.org/keywords/health-care |
| keywords[2].score | 0.522761344909668 |
| keywords[2].display_name | Health care |
| keywords[3].id | https://openalex.org/keywords/bridging |
| keywords[3].score | 0.50565505027771 |
| keywords[3].display_name | Bridging (networking) |
| keywords[4].id | https://openalex.org/keywords/confidentiality |
| keywords[4].score | 0.4790978729724884 |
| keywords[4].display_name | Confidentiality |
| keywords[5].id | https://openalex.org/keywords/language-barrier |
| keywords[5].score | 0.4688645005226135 |
| keywords[5].display_name | Language barrier |
| keywords[6].id | https://openalex.org/keywords/intensive-care |
| keywords[6].score | 0.4255700409412384 |
| keywords[6].display_name | Intensive care |
| keywords[7].id | https://openalex.org/keywords/knowledge-management |
| keywords[7].score | 0.4049435555934906 |
| keywords[7].display_name | Knowledge management |
| keywords[8].id | https://openalex.org/keywords/computer-science |
| keywords[8].score | 0.38704714179039 |
| keywords[8].display_name | Computer science |
| keywords[9].id | https://openalex.org/keywords/medicine |
| keywords[9].score | 0.3651997447013855 |
| keywords[9].display_name | Medicine |
| keywords[10].id | https://openalex.org/keywords/nursing |
| keywords[10].score | 0.320658415555954 |
| keywords[10].display_name | Nursing |
| keywords[11].id | https://openalex.org/keywords/computer-security |
| keywords[11].score | 0.18294724822044373 |
| keywords[11].display_name | Computer security |
| keywords[12].id | https://openalex.org/keywords/political-science |
| keywords[12].score | 0.10842785239219666 |
| keywords[12].display_name | Political science |
| keywords[13].id | https://openalex.org/keywords/intensive-care-medicine |
| keywords[13].score | 0.10653647780418396 |
| keywords[13].display_name | Intensive care medicine |
| language | en |
| locations[0].id | doi:10.20944/preprints202412.1686.v1 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S6309402219 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Preprints.org |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.20944/preprints202412.1686.v1 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5032346226 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Sahar Bahrami |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Sahar Bahrami |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5016024968 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-8644-1728 |
| authorships[1].author.display_name | Francesca Rubulotta |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Francesca Rubulotta |
| authorships[1].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.20944/preprints202412.1686.v1 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Artificial Intelligence-Driven Translation Tool in Intensive Care Unit (AITIC) for Enhancing Communication and Research |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11636 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9666000008583069 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2718 |
| primary_topic.subfield.display_name | Health Informatics |
| primary_topic.display_name | Artificial Intelligence in Healthcare and Education |
| related_works | https://openalex.org/W4387497383, https://openalex.org/W3183948672, https://openalex.org/W3173606202, https://openalex.org/W3110381201, https://openalex.org/W2948807893, https://openalex.org/W2935909890, https://openalex.org/W2778153218, https://openalex.org/W2758277628, https://openalex.org/W1531601525, https://openalex.org/W2350593162 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.20944/preprints202412.1686.v1 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S6309402219 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Preprints.org |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.20944/preprints202412.1686.v1 |
| primary_location.id | doi:10.20944/preprints202412.1686.v1 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S6309402219 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Preprints.org |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.20944/preprints202412.1686.v1 |
| publication_date | 2024-12-20 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 2, 25, 100 |
| abstract_inverted_index.Al | 154 |
| abstract_inverted_index.As | 24 |
| abstract_inverted_index.To | 147 |
| abstract_inverted_index.an | 72 |
| abstract_inverted_index.as | 45, 47 |
| abstract_inverted_index.be | 175 |
| abstract_inverted_index.in | 18, 37, 49, 99, 125, 140, 162 |
| abstract_inverted_index.is | 1, 78 |
| abstract_inverted_index.no | 153 |
| abstract_inverted_index.of | 27, 40, 150 |
| abstract_inverted_index.to | 4, 14, 91, 121 |
| abstract_inverted_index.ICU | 144 |
| abstract_inverted_index.Key | 116 |
| abstract_inverted_index.The | 135 |
| abstract_inverted_index.and | 9, 58, 70, 96, 102, 111, 142, 166, 192, 201 |
| abstract_inverted_index.app | 156 |
| abstract_inverted_index.are | 60, 132, 145, 169 |
| abstract_inverted_index.for | 7, 64, 80, 128, 160 |
| abstract_inverted_index.has | 157 |
| abstract_inverted_index.ill | 43 |
| abstract_inverted_index.not | 61 |
| abstract_inverted_index.our | 151 |
| abstract_inverted_index.the | 19, 38, 41, 108, 143, 148 |
| abstract_inverted_index.who | 12 |
| abstract_inverted_index.AITC | 179 |
| abstract_inverted_index.Care | 21 |
| abstract_inverted_index.ICUs | 127 |
| abstract_inverted_index.This | 84 |
| abstract_inverted_index.been | 158 |
| abstract_inverted_index.best | 149 |
| abstract_inverted_index.care | 39, 110 |
| abstract_inverted_index.data | 167 |
| abstract_inverted_index.fast | 191 |
| abstract_inverted_index.need | 3 |
| abstract_inverted_index.that | 55, 118, 173 |
| abstract_inverted_index.they | 106, 113 |
| abstract_inverted_index.tool | 77, 85 |
| abstract_inverted_index.uses | 181 |
| abstract_inverted_index.well | 46 |
| abstract_inverted_index.will | 86 |
| abstract_inverted_index.with | 185 |
| abstract_inverted_index.AITIC | 196 |
| abstract_inverted_index.ICUs. | 163 |
| abstract_inverted_index.There | 0 |
| abstract_inverted_index.could | 189, 197 |
| abstract_inverted_index.fact, | 28 |
| abstract_inverted_index.need. | 114 |
| abstract_inverted_index.offer | 190 |
| abstract_inverted_index.other | 170 |
| abstract_inverted_index.tools | 139 |
| abstract_inverted_index.units | 22 |
| abstract_inverted_index.which | 180 |
| abstract_inverted_index.(ICU). | 23 |
| abstract_inverted_index.Google | 56 |
| abstract_inverted_index.Recent | 52 |
| abstract_inverted_index.access | 92, 120 |
| abstract_inverted_index.belong | 13 |
| abstract_inverted_index.enable | 87 |
| abstract_inverted_index.enough | 63 |
| abstract_inverted_index.expand | 202 |
| abstract_inverted_index.family | 10, 35 |
| abstract_inverted_index.health | 123 |
| abstract_inverted_index.impact | 32 |
| abstract_inverted_index.issues | 172 |
| abstract_inverted_index.matter | 26 |
| abstract_inverted_index.models | 183 |
| abstract_inverted_index.should | 174 |
| abstract_inverted_index.timely | 101 |
| abstract_inverted_index.trial. | 51 |
| abstract_inverted_index.ChatGPT | 59 |
| abstract_inverted_index.Method: | 115 |
| abstract_inverted_index.Patient | 164 |
| abstract_inverted_index.dataset | 188 |
| abstract_inverted_index.digital | 137 |
| abstract_inverted_index.factors | 117 |
| abstract_inverted_index.improve | 5 |
| abstract_inverted_index.manner, | 104 |
| abstract_inverted_index.medical | 66 |
| abstract_inverted_index.members | 11 |
| abstract_inverted_index.patient | 33 |
| abstract_inverted_index.privacy | 165 |
| abstract_inverted_index.receive | 107 |
| abstract_inverted_index.safety, | 34 |
| abstract_inverted_index.studies | 53 |
| abstract_inverted_index.support | 198 |
| abstract_inverted_index.trained | 184 |
| abstract_inverted_index.Results: | 134 |
| abstract_inverted_index.accurate | 62, 193 |
| abstract_inverted_index.advanced | 65, 93, 122 |
| abstract_inverted_index.barriers | 30 |
| abstract_inverted_index.bridging | 81 |
| abstract_inverted_index.clinical | 50 |
| abstract_inverted_index.cultural | 15 |
| abstract_inverted_index.ensuring | 105 |
| abstract_inverted_index.existing | 136 |
| abstract_inverted_index.indicate | 54 |
| abstract_inverted_index.language | 29, 75, 82, 88, 129, 182, 206 |
| abstract_inverted_index.minority | 16, 89, 130, 207 |
| abstract_inverted_index.original | 203 |
| abstract_inverted_index.patients | 8, 44 |
| abstract_inverted_index.research | 98, 204 |
| abstract_inverted_index.Intensive | 20 |
| abstract_inverted_index.barriers. | 83 |
| abstract_inverted_index.developed | 159 |
| abstract_inverted_index.effective | 103 |
| abstract_inverted_index.emergency | 141 |
| abstract_inverted_index.essential | 79 |
| abstract_inverted_index.important | 171 |
| abstract_inverted_index.involving | 205 |
| abstract_inverted_index.real-time | 194 |
| abstract_inverted_index.reviewed. | 133, 146 |
| abstract_inverted_index.services, | 124 |
| abstract_inverted_index.translate | 57 |
| abstract_inverted_index.Artificial | 73 |
| abstract_inverted_index.Developing | 178 |
| abstract_inverted_index.Therefore, | 68 |
| abstract_inverted_index.addressed. | 176 |
| abstract_inverted_index.critically | 42 |
| abstract_inverted_index.deployment | 161 |
| abstract_inverted_index.developing | 69 |
| abstract_inverted_index.facilitate | 119 |
| abstract_inverted_index.facilities | 95 |
| abstract_inverted_index.healthcare | 94 |
| abstract_inverted_index.innovative | 97 |
| abstract_inverted_index.knowledge, | 152 |
| abstract_inverted_index.negatively | 31 |
| abstract_inverted_index.particular | 126 |
| abstract_inverted_index.communities | 17, 90, 131 |
| abstract_inverted_index.consolidate | 200 |
| abstract_inverted_index.information | 112 |
| abstract_inverted_index.medical/ICU | 186 |
| abstract_inverted_index.recruitment | 48 |
| abstract_inverted_index.terminology | 187 |
| abstract_inverted_index.translation | 76, 155 |
| abstract_inverted_index.Conclusions: | 177 |
| abstract_inverted_index.communities. | 208 |
| abstract_inverted_index.implementing | 71 |
| abstract_inverted_index.terminology. | 67 |
| abstract_inverted_index.translation. | 195 |
| abstract_inverted_index.communication | 6, 138 |
| abstract_inverted_index.comprehensive | 109 |
| abstract_inverted_index.participation | 36 |
| abstract_inverted_index.communication, | 199 |
| abstract_inverted_index.confidentiality | 168 |
| abstract_inverted_index.Intelligence-driven | 74 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.49000000953674316 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.21033116 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |