Biomarkers, Omics and Artificial Intelligence for Early Detection of Pancreatic Cancer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11140%2F25%3A10495438" target="_blank" >RIV/00216208:11140/25:10495438 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=KlKmj5Tyx7" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=KlKmj5Tyx7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.semcancer.2025.02.009" target="_blank" >10.1016/j.semcancer.2025.02.009</a>
Alternative languages
Result language
angličtina
Original language name
Biomarkers, Omics and Artificial Intelligence for Early Detection of Pancreatic Cancer
Original language description
Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment options are limited. Unlike other common cancers, there are no population-wide screening programmes for PDAC. Thus, early disease detection, although urgently needed, remains elusive. Individuals in certain high-risk groups are, however, offered screening or surveillance. Here we explore advances in understanding high-risk groups for PDAC and efforts to implement biomarker-driven detection of PDAC in these groups. We review current approaches to early detection biomarker development and the use of artificial intelligence as applied to electronic health records (EHRs) and social media. Finally, we address the cost-effectiveness of applying biomarker strategies for early detection of PDAC.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Seminars in Cancer Biology
ISSN
1044-579X
e-ISSN
1096-3650
Volume of the periodical
111
Issue of the periodical within the volume
June
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
76-88
UT code for WoS article
001441748100001
EID of the result in the Scopus database
2-s2.0-85219081949