Researchers at the University of California, Los Angeles (UCLA) have developed, FocalNet to help radiologists improve their ability to diagnose prostate cancer.
About:
Objective: FocalNet is a new artificial intelligence (AI) system to help radiologists improve their ability to diagnose ‘prostate cancer’ by evaluating magnetic resonance imaging (MRI) scans with nearly the same level of accuracy as experienced radiologists.
Working:
FocalNet uses an algorithm that comprises more than a million trainable variables.
The team trained the system by having it analyse MRI scans of 417 men with prostate cancer. Scans were fed into the system so that it could learn to assess and classify tumours in a consistent way and have it compare the results to the actual pathology specimen.
Significance: This could save time and provide guidance to less-experienced radiologists.
Radiologists use MRI to detect malignant prostate tumours. However, it takes practicing on thousands of scans to accurately determine whether a tumour is cancerous or benign.
In addition, many hospitals do not have the resources to implement the highly specialised training required for detecting cancer from MRIs.
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