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Correspondence to Author: Dortya Taján, 

Faculty of Medicine, University of Prishtina.

Introduction: Depending on the severity of the condition, the clinical course of acute pancreatitis (AP) might vary, and it is essential to estimate the likelihood of organ failure in order to start appropriate treatment and care as soon as possible. As a result, individuals who may be at high risk ought to be admitted to a high dependence unit. Three choices are available to us for risk assessment: (1) Severe AP can be predicted using univariate biochemical indicators. One of their primary traits is that the results of AP are impacted in a dose-dependent manner by the presence or lack of these variables. Sadly, due to their poor accuracy, none of these measures can be applied in clinical settings. (2) Score systems that use four to twenty-five parameters have been created to predict severity. They typically call for a number of parameters that are not measured every day, and they frequently take longer than twenty-four hours to complete, wasting crucial time. However, because these scores only use binary values, they lose information even though they potentially predict specific organ failure or severity. Their application in therapeutic settings is therefore restricted. (3) Complex nonlinear correlations between many biochemical indicators and disease outcomes can be identified by artificial intelligence. Recently, we created EASY-APP, the first user-friendly tool that makes use of several continuous variables that are accessible at the moment of admission. The web-based tool can be used quickly and easily upon admission because it does not require all of the parameters for prediction. Artificial intelligence should be used in the future to create prognostic scores in order to prevent data loss and offer a more customized risk assessment.

Keywords:machine learning; albumin; CRP; WBC; BISAP; mortality; severity.

Citation:

Dortya Taján. Artificial Intelligence Is Time To Use For Predicting The Severity Of Acute Pancreatitis.. Journal Of Acute Pancreatitis 2025.