Artificial Intelligence Uses Patient Data to Anticipate Cancer Outcomes

Artificial intelligence trends are important to look out for in the global healthcare in a long run

A new study shows how artificial intelligence uses patient data to predict outcomes associated with 14 types of cancer.  

A study from the Mahmood Lab at Brigham and Women’s Hospital revealed how artificial intelligence (AI) uses factors such as patient history and gene pathology to identify and anticipate potential cancer outcomes.  

This research team consistently prioritized accuracy through the consistent use of various types of diagnostic information. 

They also constructed the AI model with the assistance of The Cancer Genome Atlas (TCGA), which provided information on various types of cancer and develop algorithm.

After the application of the model, researchers determined that it had the ability to predict outcomes better than those that use single sources.

“This work sets the stage for larger healthcare AI studies that combine data from multiple sources,” said Mahmood. 

In a broader sense, our findings emphasize a need for building computational pathology prognostic models with much larger datasets and downstream clinical trials to establish utility. 

Various studies from the past have shared methods regarding the implementation of AI into predictive analytics.