Colorectal cancer (CRC) is a major health issue worldwide. It's becoming more common in younger people. This is partly because of better screening. However, most prediction tools for CRC are based on older adults. This limits their use for younger and more diverse groups. The role of diet in preventing and managing CRC is getting more attention. But, using computers to study how diet affects CRC is still new.

A fresh approach has been developed. It combines natural language processing (NLP) with advanced language models. This is called the Nutritional Impact on CRC Prediction Framework. It aims to provide new insights into how diet affects CRC care in different populations.

The research used a large dataset. It included over 1000 people from various regions. The data was a mix of structured and unstructured information. This included details about food ingredients. The text was cleaned up using standard methods. This involved removing unnecessary words, making all letters lowercase, and getting rid of punctuation. Key terms were then pulled out and shown in a word cloud.

The dataset had an imbalance. There were more non-CRC cases than CRC cases. To fix this, a technique called random oversampling was used. This evens out the numbers, making the data more reliable.

The cleaned data was then analyzed using advanced language models. These models identified key nutritional factors. They also predicted whether someone had CRC or not based on their diet. The results were impressive. The combination of NLP and these models boosted prediction accuracy to 98. 4%. Sensitivity was 97. 6%, specificity was 96. 9%, and the F1-Score was 96. 2%. This means the model is very good at making correct predictions with few mistakes.

This new framework is a big step forward. It offers a data-driven way to understand how diet affects CRC. This can help doctors make better predictions and give personalized dietary advice. It's a promising tool for improving CRC care.

Diet's Role in Colorectal Cancer: A New Approach

Actions