Artificial intelligence models assisting physicians in quantifying pancreatic necrosis in acute pancreatitis.

ABSTRACT:

Background

Acute pancreatitis (AP) is a potentially life-threatening condition characterized by inflammation of the pancreas, which can lead to complications such as pancreatic necrosis. The modified computed tomography severity index (MCTSI) is a widely used tool for assessing the severity of AP, particularly the extent of pancreatic necrosis. The accurate and timely assessment of the necrosis volume is crucial in guiding treatment decisions and improving patient outcomes. However, the current diagnostic process relies heavily on the manual interpretation of computed tomography (CT) scans, which can be subjective and prone to variability among clinicians. This study aimed to develop a deep-learning network model to assist clinicians in diagnosing the volume ratio of pancreatic nec

SUBMITTER: Lu CX 

PROVIDER: S-EPMC11744103 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature