EURO 2025 Leeds
Abstract Submission

2930. Applications of decision support systems in medicine

Contributed abstract in session MA-56: Computational Biology & Healthcare, stream Computational Biology, Bioinformatics and Medicine.

Monday, 8:30-10:00
Room: Liberty 1.11

Authors (first author is the speaker)

1. Piotr Lukasiak
Institute of Computing Science, Poznan University of Technology
2. Maciej Majchrzak
Poznan University of Technology

Abstract

Decision support systems are playing an increasingly important role in medical data analysis, as the ability to analyse data and explore the rules governing the phenomena is becoming crucial in diagnosis and prevention. In this study, the focus was on two areas: liver analysis and head injury analysis.
The liver plays a key role in maintaining overall health, and the implementation of appropriate dietary and lifestyle choices is of paramount importance to ensure its optimal functioning. Early recognition of hepatic steatosis and hepatic fibrosis is crucial for effective management and prevention of liver dysfunction.The aim of this study was to demonstrate that routine clinical tests, augmented with machine learning algorithms, are able to provide sufficient data to predict critical endpoints.The proposed FibrAIm tool facilitates the identification of patients who, despite the absence of abnormal laboratory results, may already have severe fibrosis.
Another application of machine learning we have designed is the prediction of head injury types based on medical imaging data. The tool designed in this study, based on neural network models, enables efficient diagnosis of various head injuries, reducing the risk of complications and providing an effective and efficient decision support system in hospital emergency departments.
In both cases, the effectiveness of the methodology implemented and designed was confirmed by the analyses and experiments carried out.

Keywords

Status: accepted

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