Assessment of Prostate and Bladder Cancer Genomic Biomarkers Using Artificial Intelligence: a Systematic Review
Language English Country United States Media print-electronic
Document type Systematic Review, Journal Article, Review
PubMed
38099997
DOI
10.1007/s11934-023-01193-2
PII: 10.1007/s11934-023-01193-2
Knihovny.cz E-resources
- Keywords
- Artificial intelligence, Bladder cancer, Differentially expressed genes, Genomics, Prostate cancer,
- MeSH
- Biomarkers MeSH
- Humans MeSH
- Neoplasm Recurrence, Local genetics MeSH
- Urinary Bladder Neoplasms * diagnosis genetics therapy MeSH
- Prostate * MeSH
- Recurrence MeSH
- Artificial Intelligence MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
- Systematic Review MeSH
- Names of Substances
- Biomarkers MeSH
PURPOSE OF REVIEW: The aim of the systematic review is to assess AI's capabilities in the genetics of prostate cancer (PCa) and bladder cancer (BCa) to evaluate target groups for such analysis as well as to assess its prospects in daily practice. RECENT FINDINGS: In total, our analysis included 27 articles: 10 articles have reported on PCa and 17 on BCa, respectively. The AI algorithms added clinical value and demonstrated promising results in several fields, including cancer detection, assessment of cancer development risk, risk stratification in terms of survival and relapse, and prediction of response to a specific therapy. Besides clinical applications, genetic analysis aided by the AI shed light on the basic urologic cancer biology. We believe, our results of the AI application to the analysis of PCa, BCa data sets will help to identify new targets for urological cancer therapy. The integration of AI in genomic research for screening and clinical applications will evolve with time to help personalizing chemotherapy, prediction of survival and relapse, aid treatment strategies such as reducing frequency of diagnostic cystoscopies, and clinical decision support, e.g., by predicting immunotherapy response. These factors will ultimately lead to personalized and precision medicine thereby improving patient outcomes.
Clinical Institute for Children Health Named After N F Filatov Sechenov University Moscow Russia
Department of Surgery S H Ho Urology Centre The Chinese University of Hong Kong Hong Kong China
Department of Urology 2nd Faculty of Medicine Charles University Prague Czech Republic
Department of Urology Clinico San Carlos University Hospital Madrid Spain
Department of Urology University Hospital Southampton Southampton United Kingdom
Department of Urology University of Texas Southwestern Dallas TX USA
Department of Urology Weill Cornell Medical College New York NY USA
Division of Urology Rabin Medical Center Petah Tikva Israel
Institute for Urology and Reproductive Health Sechenov University Moscow Russia
Institute of Molecular Theranostics Sechenov University Moscow Russia
Karl Landsteiner Institute of Urology and Andrology Vienna Austria
School of Medicine Brady Urological Institute Johns Hopkins Medicine Baltimore MD USA
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