Achieving Inclusive Healthcare through Integrating Education and Research with AI and Personalized Curricula
Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of compu...
Saved in:
Published in | medRxiv : the preprint server for health sciences |
---|---|
Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.08.2024
|
Online Access | Get more information |
Cover
Loading…
Abstract | Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of computational experts, engineers, designers, and healthcare professionals to develop user-friendly systems and shared terminologies. The widespread adoption of large language models (LLMs) like GPT-4 and Claude 3 highlights the importance of making complex data accessible to non-specialists. The Stanford Data Ocean (SDO) strives to mitigate these challenges through a scalable, cloud-based platform that supports data management for various data types, advanced research, and personalized learning in precision medicine. SDO provides AI tutors and AI-powered data visualization tools to enhance educational and research outcomes and make data analysis accessible for users from diverse educational backgrounds. By extending engagement and cutting-edge research capabilities globally, SDO particularly benefits economically disadvantaged and historically marginalized communities, fostering interdisciplinary biomedical research and bridging the gap between education and practical application in the biomedical field. |
---|---|
AbstractList | Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of computational experts, engineers, designers, and healthcare professionals to develop user-friendly systems and shared terminologies. The widespread adoption of large language models (LLMs) like GPT-4 and Claude 3 highlights the importance of making complex data accessible to non-specialists. The Stanford Data Ocean (SDO) strives to mitigate these challenges through a scalable, cloud-based platform that supports data management for various data types, advanced research, and personalized learning in precision medicine. SDO provides AI tutors and AI-powered data visualization tools to enhance educational and research outcomes and make data analysis accessible for users from diverse educational backgrounds. By extending engagement and cutting-edge research capabilities globally, SDO particularly benefits economically disadvantaged and historically marginalized communities, fostering interdisciplinary biomedical research and bridging the gap between education and practical application in the biomedical field. |
Author | Miller, Alison Derbenwick Lai, Jaslene Akhavan-Sarraf, Ramin Goncalves, Francesca Wang, Meng Monte, Emma Alavi, Arash Dixit, Amit Akbari, Ilya McGhee, Eva M Kundaje, Anshul Edmiston, Scott Tondar, Abtin Saxman, Paul Cha, Kexin Rodriguez, David Jose Florez Yracheta, Joseph Babu, Mohan Yegnashankaran, Kritika Zhou, Xin Snyder, Michael Rose, Sophia Miryam Schüssler-Fiorenza Than, Jennifer Li Pook Ross, Antony Nebeker, Camille Park, Ryan Zhang, Xinyue Contrepois, Kévin Wu, Joseph C Ma, Shirley Bahmani, Amir Dale, Kali Nair, Ramesh |
Author_xml | – sequence: 1 givenname: Amir orcidid: 0000-0003-4533-9334 surname: Bahmani fullname: Bahmani, Amir – sequence: 2 givenname: Kexin surname: Cha fullname: Cha, Kexin – sequence: 3 givenname: Arash orcidid: 0000-0002-7245-6889 surname: Alavi fullname: Alavi, Arash – sequence: 4 givenname: Amit surname: Dixit fullname: Dixit, Amit – sequence: 5 givenname: Antony surname: Ross fullname: Ross, Antony – sequence: 6 givenname: Ryan surname: Park fullname: Park, Ryan – sequence: 7 givenname: Francesca surname: Goncalves fullname: Goncalves, Francesca – sequence: 8 givenname: Shirley surname: Ma fullname: Ma, Shirley – sequence: 9 givenname: Paul surname: Saxman fullname: Saxman, Paul – sequence: 10 givenname: Ramesh surname: Nair fullname: Nair, Ramesh – sequence: 11 givenname: Ramin surname: Akhavan-Sarraf fullname: Akhavan-Sarraf, Ramin – sequence: 12 givenname: Xin surname: Zhou fullname: Zhou, Xin – sequence: 13 givenname: Meng surname: Wang fullname: Wang, Meng – sequence: 14 givenname: Kévin surname: Contrepois fullname: Contrepois, Kévin – sequence: 15 givenname: Jennifer Li Pook surname: Than fullname: Than, Jennifer Li Pook – sequence: 16 givenname: Emma surname: Monte fullname: Monte, Emma – sequence: 17 givenname: David Jose Florez surname: Rodriguez fullname: Rodriguez, David Jose Florez – sequence: 18 givenname: Jaslene surname: Lai fullname: Lai, Jaslene – sequence: 19 givenname: Mohan surname: Babu fullname: Babu, Mohan – sequence: 20 givenname: Abtin surname: Tondar fullname: Tondar, Abtin – sequence: 21 givenname: Sophia Miryam Schüssler-Fiorenza surname: Rose fullname: Rose, Sophia Miryam Schüssler-Fiorenza – sequence: 22 givenname: Ilya surname: Akbari fullname: Akbari, Ilya – sequence: 23 givenname: Xinyue surname: Zhang fullname: Zhang, Xinyue – sequence: 24 givenname: Kritika surname: Yegnashankaran fullname: Yegnashankaran, Kritika – sequence: 25 givenname: Joseph surname: Yracheta fullname: Yracheta, Joseph – sequence: 26 givenname: Kali surname: Dale fullname: Dale, Kali – sequence: 27 givenname: Alison Derbenwick surname: Miller fullname: Miller, Alison Derbenwick – sequence: 28 givenname: Scott surname: Edmiston fullname: Edmiston, Scott – sequence: 29 givenname: Eva M surname: McGhee fullname: McGhee, Eva M – sequence: 30 givenname: Camille surname: Nebeker fullname: Nebeker, Camille – sequence: 31 givenname: Joseph C surname: Wu fullname: Wu, Joseph C – sequence: 32 givenname: Anshul surname: Kundaje fullname: Kundaje, Anshul – sequence: 33 givenname: Michael orcidid: 0000-0003-0784-7987 surname: Snyder fullname: Snyder, Michael |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39211867$$D View this record in MEDLINE/PubMed |
BookMark | eNqFjssKwjAURLNQfP-C5AdcVMHHspRKuxNxX67JtQmkSblJKvr1VtG1qxnmnMVM2cA6iyM23hzWSbLf7ibMpEJp7LSteWmFiV53yAsEE5QAQh4UuVirHgasCcJbzGUUfXOWg5X8jB6BhOJ3HRRPy894QvLOgtFPlDyLRFpEA3M2vIHxuPjmjC2P-SUrVm28NiirlnQD9Kh-99Z_hRdRTEQK |
ContentType | Journal Article |
DBID | NPM |
DatabaseName | PubMed |
DatabaseTitle | PubMed |
DatabaseTitleList | PubMed |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | no_fulltext_linktorsrc |
ExternalDocumentID | 39211867 |
Genre | Preprint Journal Article |
GroupedDBID | NPM |
ID | FETCH-pubmed_primary_392118672 |
IngestDate | Sat Nov 02 12:18:00 EDT 2024 |
IsPeerReviewed | false |
IsScholarly | false |
Language | English |
LinkModel | OpenURL |
MergedId | FETCHMERGED-pubmed_primary_392118672 |
ORCID | 0000-0002-7245-6889 0000-0003-4533-9334 0000-0003-0784-7987 |
PMID | 39211867 |
ParticipantIDs | pubmed_primary_39211867 |
PublicationCentury | 2000 |
PublicationDate | 2024-Aug-01 |
PublicationDateYYYYMMDD | 2024-08-01 |
PublicationDate_xml | – month: 08 year: 2024 text: 2024-Aug-01 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | medRxiv : the preprint server for health sciences |
PublicationTitleAlternate | medRxiv |
PublicationYear | 2024 |
Score | 3.8614247 |
Snippet | Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary... |
SourceID | pubmed |
SourceType | Index Database |
Title | Achieving Inclusive Healthcare through Integrating Education and Research with AI and Personalized Curricula |
URI | https://www.ncbi.nlm.nih.gov/pubmed/39211867 |
hasFullText | |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1ba8IwFMfD3GD4MjZ2v0ge9lY6sDf1sbgN3VDGcOCbpFmKAa3iOhE__U6uLTLZ5SWUJC2hv7Y5PTn_E4Ru_aQhBLp116de6AZRGrotljIXcCctj7AWSYU4udePOm_B0zAcFtvcSXVJntzR9be6kv9QhTrgKlSyfyBrLwoVcAx8oQTCUP6KcUzHnC3Vmj-dfMpI9E4R0GX24OnqlBCiow3o0MpE7fWQ7ti4q7QDxj5fC--vdhGSshULM-jrii8dExQyF6kxeZY7wsXLFjJ0UQksHT3DFs54Mp6qbaSceMptZHBbrTs9sxW3T2s8IUvVcUE-rNf6nq94rk_Pyz4LL7ARc3mJynwqsYCBVhdZ9X5u3UiMbZoqqNJoik9c_6VXRfumeuM_QdoLg0N0oA19HCtqR2iHZcdoYolhSwwXxLAmhkvEsCWGAQ42xLAghuOurCwTw5bYCao9PgzaHVcNcDRXiUVGZujeKdrNZhk7R5hGTcr895T4HgmCgJIGJWnQ9OtRyFhE_Qt0tuUil1tbrlC1gHKN9lJ4HdgN2FZ5UpN38Qv-HTRO |
link.rule.ids | 783 |
linkProvider | National Library of Medicine |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Achieving+Inclusive+Healthcare+through+Integrating+Education+and+Research+with+AI+and+Personalized+Curricula&rft.jtitle=medRxiv+%3A+the+preprint+server+for+health+sciences&rft.au=Bahmani%2C+Amir&rft.au=Cha%2C+Kexin&rft.au=Alavi%2C+Arash&rft.au=Dixit%2C+Amit&rft.date=2024-08-01&rft_id=info%3Apmid%2F39211867&rft_id=info%3Apmid%2F39211867&rft.externalDocID=39211867 |