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TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20250822T115810Z
LOCATION:Room 6.0D13
DTSTART;TZID=Europe/Stockholm:20250617T120000
DTEND;TZID=Europe/Stockholm:20250617T123000
UID:submissions.pasc-conference.org_PASC25_sess143_msa245@linklings.com
SUMMARY:Challenges in Integrating Computing-Based Solutions in Translation
 al Biomedicine
DESCRIPTION:Hugo Hernandez (spinTwo)\n\nIntegrating computing-based soluti
 ons into translational biomedicine presents significant challenges, partic
 ularly in healthcare institutions underlying technical infrastructure and 
 the adaptation of these solutions. Many facilities, especially in remote a
 reas, lack infrastructure such as computing rooms and robust datacenters t
 o support high-performance computing (HPC) systems required to handle the 
 massive volumes of diverse generated biomedical data due to budget restrai
 nts preventing investment in cutting-edge technology. Secured AI tools mus
 t be tailored to complex clinical workflows, requiring resources for custo
 mization, testing, and regulatory compliance. Network reliability and cybe
 rsecurity issues complicate integration efforts for deploying AI-driven so
 lutions. Data exchange across systems is hindered by fragmented sources, i
 nteroperability challenges, and varying data formats. The mix of structure
 d and unstructured data, such as clinical records or genomic data, complic
 ates integration. Data governance is a concern, especially regarding patie
 nt privacy, regulatory compliance like HIPAA, and ensuring ethical use of 
 AI tools. For remote ICUs, limited bandwidth and the need for real-time de
 cision-making add pressure, where delays can have critical consequences. O
 vercoming these physical, technical, and financial barriers, along with ad
 dressing the complexities in infrastructure, dataflow, and governance comp
 lexities, is crucial for successful integration of AI in healthcare and re
 alizing its potential in improving patient care and outcomes.\n\nDomain: A
 pplied Social Sciences and Humanities, Engineering, Life Sciences, Computa
 tional Methods and Applied Mathematics\n\nSession Chair: John Anderson Gar
 cia Henao (Balgrist University Hospital, OR-X Translational Center for Sur
 gery)\n\n
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