Linköping University researchers demonstrated the results of their study on the use of artificial intelligence (AI) in healthcare. They highlighted the potential of artificial neural networks to find out patterns in tremendous amounts of gene expression data. Moreover, the research team also underlined the importance of this network to uncover the disease-related genes groups.
Tapping New Ways for Precision Medicine and Individualized Treatment
Researchers discovered a unique method that can assist in future precision medicine and personalized patient treatment. Furthermore, the study is open for access in the journal Nature Communications. The key focus of this research is to form the biological network maps with the help of AI. The base of these maps is the technique by which all diverse genes or proteins communicate with each other. Besides, the study employs AI to tap the possibility of finding out biological networks with the help of deep learning.
In deep learning, “artificial neural networks” are trained using the available experimental data. Additionally, such types of networks find use in various applications including image recognition. The key reason for the same is their efficiency to find out patterns in huge and complicated data. However, the use of machine learning techniques is rare in biological studies. Sanjiv Dwivedi from Linköping University stated, “For the first time, we have employed deep learning to discover disease-related genes. The technique is powerful in the analysis of big amounts of biological information.”
The researchers studied the usability of gene expression models to check the connection between gene expression patterns and diseases. Moreover, the study verified the dependability of the model to find out associated patterns that support the body’s biological mechanism. Mika Gustafsson is the lead author of this study. He stated that the close association with medical scientists will open the doors for the implementation of the latest method in precision medicine.