Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?
Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may...
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MDPI AG
2025-03-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/13/4/836 |
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| author | Maja Mejza Anna Bajer Sora Wanibuchi Ewa Małecka-Wojciesko |
| author_facet | Maja Mejza Anna Bajer Sora Wanibuchi Ewa Małecka-Wojciesko |
| author_sort | Maja Mejza |
| collection | DOAJ |
| description | Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may be appropriate for screening is new-onset diabetes (NOD) patients. Such a conclusion stems from the fact that pancreatic cancer can cause diabetes several months before diagnosis. The most widely used screening tool for this population, the ENDPAC (Enriching New-Onset Diabetes for Pancreatic Cancer) model, has not achieved satisfactory results in validation trials. This provoked the first attempts at using artificial intelligence (AI) to create larger, multi-parameter models that could better identify the at-risk population, which would be suitable for screening. The results shown by the authors of these trials seem promising. Nonetheless, the number of publications is limited, and the downfalls of using AI are not well highlighted. This narrative review presents a summary of previous publications, recent advancements and feasible solutions for effective screening of patients with NOD for pancreatic cancer. |
| format | Article |
| id | doaj-art-53a5ca5446804e2bb778aaac298ee090 |
| institution | OA Journals |
| issn | 2227-9059 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Biomedicines |
| spelling | doaj-art-53a5ca5446804e2bb778aaac298ee0902025-08-20T02:28:19ZengMDPI AGBiomedicines2227-90592025-03-0113483610.3390/biomedicines13040836Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?Maja Mejza0Anna Bajer1Sora Wanibuchi2Ewa Małecka-Wojciesko3Department of Digestive Tract Diseases, Medical University of Lodz, 90-153 Lodz, PolandDepartment of Digestive Tract Diseases, Medical University of Lodz, 90-153 Lodz, PolandAichi Medical University Hospital, Nagakute 480-1195, JapanDepartment of Digestive Tract Diseases, Medical University of Lodz, 90-153 Lodz, PolandPancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may be appropriate for screening is new-onset diabetes (NOD) patients. Such a conclusion stems from the fact that pancreatic cancer can cause diabetes several months before diagnosis. The most widely used screening tool for this population, the ENDPAC (Enriching New-Onset Diabetes for Pancreatic Cancer) model, has not achieved satisfactory results in validation trials. This provoked the first attempts at using artificial intelligence (AI) to create larger, multi-parameter models that could better identify the at-risk population, which would be suitable for screening. The results shown by the authors of these trials seem promising. Nonetheless, the number of publications is limited, and the downfalls of using AI are not well highlighted. This narrative review presents a summary of previous publications, recent advancements and feasible solutions for effective screening of patients with NOD for pancreatic cancer.https://www.mdpi.com/2227-9059/13/4/836PDACNODpancreatic ductal adenocarcinomaartificial intelligencediabetes mellitusdeep learning |
| spellingShingle | Maja Mejza Anna Bajer Sora Wanibuchi Ewa Małecka-Wojciesko Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? Biomedicines PDAC NOD pancreatic ductal adenocarcinoma artificial intelligence diabetes mellitus deep learning |
| title | Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? |
| title_full | Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? |
| title_fullStr | Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? |
| title_full_unstemmed | Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? |
| title_short | Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes? |
| title_sort | can ai be useful in the early detection of pancreatic cancer in patients with new onset diabetes |
| topic | PDAC NOD pancreatic ductal adenocarcinoma artificial intelligence diabetes mellitus deep learning |
| url | https://www.mdpi.com/2227-9059/13/4/836 |
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