Genomic and Health Data as Fuel to Advance a Health Data Economy for Artificial Intelligence.
Cloud and distributed computing, code repositories, and large language models are democratizing the less computationally intensive use cases of artificial intelligence (AI) in medicine. The convergence and democratization of these powerful tools promises to mobilize and utilize humanity's knowledge...
| Publicado en: | BioMed Research International Vol. 2025; pp. 1 - 12 |
|---|---|
| Autores principales: | , , , |
| Formato: | review Journal Article |
| Publicado: |
Wiley-Blackwell
7/19/2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186809710&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186809710 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 7/19/2025 vid: 2025 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 186809710 186809710 186809710 10.1155/bmri/6565955 186809710 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Genomic and Health Data as Fuel to Advance a Health Data Economy for Artificial Intelligence. aug: au: Silva, Patrick J. Silva, Patrick A. Ramos, Kenneth S. Shahmy, Seyed affil: Institute for Bioscience and Technology,, Texas A&M University,, Houston, Texas,, USA, tamu.edu sug: subj: Artificial Intelligence Genomics Medical Records Patient Centered Care Communication Health Care Delivery Trust Knowledge Bases Goals and Objectives Blockchain Intellectual Property ab: Cloud and distributed computing, code repositories, and large language models are democratizing the less computationally intensive use cases of artificial intelligence (AI) in medicine. The convergence and democratization of these powerful tools promises to mobilize and utilize humanity's knowledge and data, at least the knowledge bases and data that are readily available in the public commons. Healthcare represents a challenge due to fragmentation of the data fabric and governance mechanisms intrinsic to that sector of the economy. Privacy laws, stewardship practices, and the fragmented nature of the patient data journey (medical record silos) create cumbersome impediments to health data sharing, particularly longitudinal patient‐level data. Consequently, obtaining the data necessary to train and operationalize AI in many healthcare and clinical genomics use cases limits the promise of these new technologies in addressing complexities in healthcare. We posit that trust, provenance, and fitness of health data and transaction costs represent challenges that blockchain ledgers and smart digital contracts might address. Here, we present frameworks from some of the great economic thinkers that might help address some of the stewardship and agency issues inherent to health data sharing. Our goal is to promote a more equitable and patient‐centric healthcare data fabric to address current challenges of healthcare. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|