AI will find linkages between diseases

Scientists from King Abdullah University of Science and Technology (KAUST) have developed a tool based on artificial intelligence.

This new tool will help identify hidden links between various diseases in the future.

The discovery, published in the journal Bioinformatics, could lead to new strategies for treating and preventing diseases.

The tool uses natural language processing to analyze medical literature and real patient data.

It identifies cause-and-effect relationships, such as how hypertension can lead to heart failure.

This approach helps to better understand disease mechanisms and identify common risk factors.

The KAUST team approaches disease management not as independent problems, but as interrelated conditions.

This helps to find common risks and improve the accuracy of disease prediction.

Its ability to not just find links between diseases, but to identify which diseases can lead to others.

For example, type 2 diabetes can lead to high blood sugar levels, which causes small vessel disease.

This knowledge helps treat the primary disease to prevent complications.

The tool also improves the accuracy of polygenic risk calculations, which assess genetic predisposition to disease.

It helps account for how a single genetic variant can affect multiple diseases, which improves prediction for complex diseases.