Pancreatic cyst classification

The present invention relates to computer-implemented methods for determining if a pancreatic cyst of a subject is pre-malignant/malignant or benign using protein abundance data obtained from a liquid sample from the subject. Methods for selecting a treatment for a subject having a pancreatic cyst, and treating a subject having a malignant pancreatic cyst are also provided.

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Publication Details

Journal
Repository@Hull (Worktribe) (University of Hull)
Published
2025-09-18
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
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Pancreatic cyst classification

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Repository@Hull (Worktribe) (University of Hull)
Machine Learning in Bioinformatics
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Pancreatic cyst classification

Darragh Patrick O'Brien, David Kuang-Fu Chang, Benedikt Mathias Alfred Kessler, Anthony Maraveyas, Dimitrios Manolis, Leonid Nikitenko
article en

Abstract

The present invention relates to computer-implemented methods for determining if a pancreatic cyst of a subject is pre-malignant/malignant or benign using protein abundance data obtained from a liquid sample from the subject. Methods for selecting a treatment for a subject having a pancreatic cyst, and treating a subject having a malignant pancreatic cyst are also provided.

Repository@Hull (Worktribe) (University of Hull)
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Machine Learning in Bioinformatics
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Pancreatic cyst classification — Darragh Patrick O'Brien, David Kuang-Fu Chang, et al. · Repository@Hull (Worktribe) (University of Hull) (2025) | TGRS Research Map | TGRS