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Background: Cancer remains a significant health challenge in the ASEAN region, highlighting the need for effective screening programs. However, approaches, target demographics, and intervals vary across ASEAN member states, necessitating a comprehensive understanding of these variations to assess program effectiveness. Additionally, while artificial intelligence (AI) holds promise as a tool for cancer screening, its utilization in the ASEAN region is unexplored.
Purpose: This study aims to identify and evaluate different cancer screening programs across ASEAN, with a focus on assessing the integration and impact of AI in these programs.
Methods: A scoping review was conducted using PRISMA-ScR guidelines to provide a comprehensive overview of cancer screening programs and AI usage across ASEAN. Data were collected from government health ministries, official guidelines, literature databases, and relevant documents. The use of AI in cancer screening reviews involved searches through PubMed, Scopus, and Google Scholar with the inclusion criteria of only included studies that utilized data from the ASEAN region from January 2019 to May 2024.
Results: The findings reveal diverse cancer screening approaches in ASEAN. Countries like Myanmar, Laos, Cambodia, Vietnam, Brunei, Philippines, Indonesia and Timor-Leste primarily adopt opportunistic screening, while Singapore, Malaysia, and Thailand focus on organized programs. Cervical cancer screening is widespread, using both opportunistic and organized methods. Fourteen studies were included in the scoping review, covering breast (5 studies), cervical (2 studies), colon (4 studies), hepatic (1 study), lung (1 study), and oral (1 study) cancers. Studies revealed that different stages of AI integration for cancer screening: prospective clinical evaluation (50%), silent trial (36%) and exploratory model development (14%), with promising results in enhancing cancer screening accuracy and efficiency.
Conclusion: Cancer screening programs in the ASEAN region require more organized approaches targeting appropriate age groups at regular intervals to meet the WHO's 2030 screening targets. Efforts to integrate AI in Singapore, Malaysia, Vietnam, Thailand, and Indonesia show promise in optimizing screening processes, reducing costs, and improving early detection. AI technology integration enhances cancer identification accuracy during screening, improving early detection and cancer management across the ASEAN region.
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http://dx.doi.org/10.1186/s12885-025-14026-x | DOI Listing |
Eur J Gastroenterol Hepatol
September 2025
Background: Prior studies have implicated diabetes as a risk factor for pancreatic cancer, yet the impact of diabetes progression on pancreatic cancer incidence remains unclear. We aim to assess pancreatic cancer risk across different stages of diabetes.
Methods: Employing a predefined search strategy, we conducted a literature review of electronic databases up to 29 February 2024.
JCO Precis Oncol
September 2025
Cell Biology and Biotherapy Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, Napoli, Italy.
Purpose: Tumor comprehensive genomic profiling (CGP) may detect potential germline pathogenic/likely pathogenic (P/LP) alterations as secondary findings. We analyzed the frequency of potentially germline variants and large rearrangements (LRs) in the RATIONAL study, an Italian multicenter, observational clinical trial that collects next-generation sequencing-based tumor profiling data, and evaluated how these findings were managed by the enrolling centers.
Patients And Methods: Patients prospectively enrolled in the pathway-B of the RATIONAL study and undergoing CGP with the FoundationOne CDx assays were included in the analysis.
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFArq Bras Cir Dig
September 2025
Universidade de São Paulo, Faculty of Medicine, Department of Gastroenterology, Colonoscopy Division - São Paulo (SP), Brazil.
Background: Artificial intelligence (AI)-assisted colonoscopy has emerged as a tool to enhance adenoma detection rates (ADRs) and improve lesion characterization. However, its performance in real-world settings, especially in developing countries, remains uncertain.
Aims: The aim of this study was to evaluate the impact of AI on ADRs and its concordance with histopathological diagnosis.
Bioinformatics
September 2025
The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Motivation: Drug repositioning presents a streamlined and cost-efficient way to expand the range of therapeutic possibilities. Drugs with human genetic evidence are more likely to advance successfully through clinical trials towards FDA approval. Single gene-based drug repositioning methods have been implemented, but approaches leveraging a broad spectrum of molecular signatures remain underexplored.
View Article and Find Full Text PDF