Neural Network Model for Predicting Progression of Disease
Neural Network Model for Predicting Progression of Disease

Summary/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.

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