Neural Network Model for Predicting Progression of Disease
Year: 2024
Type: article
Abstract: This study investigates the use of neural network and their ability to predict disease progression based on clinical data and biomarkers. Using deep neural networks, a model was developed that efficiently analyzes the complex relationship between various factors and predict the probability of disease. The model was validated using retrospective analysis which indicated a good predictive ability that could be further utilized in better diagnostics and personalized treatment methods. More importantly, reserch detected specific pattern in the data, which enabled a more accurate prediction of disease at different stages. The study tried to improve a model by fine-tuned neural networks and tested other frameworks to gain the highets precision. This research also provides a basic for future work in directing the development of personalized therapeutic approaches based on individual patient characteristics.
Source: TEM Journal
DOI: 10.18421/tem133-09
Authors: Zvezdan Stojanović, Elvir Čajić, Dario Galić
Institution: University of Osijek
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $647
OpenAlex ID: W4401933865