AI Outperforms Clinicians in Predicting Brain Cancer Outcomes
Researchers at King’s College London have developed an artificial intelligence (AI) system that outperforms clinicians in predicting brain cancer patient outcomes. The study, published in the journal Nature Medicine, demonstrates that the AI system can predict survival, treatment response, and disease progression more accurately than current clinical methods, potentially revolutionizing healthcare by enhancing diagnostic accuracy and treatment planning.
Combining Radiomics and Genomics Data
The AI system combines radiomics and genomics data to make predictions. Radiomics refers to the extraction of features from medical imaging data, while genomics deals with the study of genes and their functions. The researchers analyzed over 10,000 magnetic resonance imaging (MRI) scans and genomic data from over 2,000 patients with gliomas, the most common type of brain cancer.
Improving Personalized Treatment Plans
By leveraging this large dataset, the AI system was able to identify patterns and biomarkers that can inform personalized treatment plans for glioma patients. The system’s predictions can help clinicians make more informed decisions about the best course of treatment, which could lead to improved outcomes for patients. The research at King’s College London showcases how combining different types of data, such as radiomics and genomics, can lead to more precise predictions and personalized care. The development of such AI systems could significantly improve the prognosis and quality of life for cancer patients in the future.
