The U.S. National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is exploring the application of AI in healthcare to enhance screening and analytical capabilities, according to Keyvan Farahani, Senior Director of Data Science, Imaging, and AI Programs at NHLBI.

Farahani believes AI could significantly advance disease prevention, diagnosis, and treatment. However, this potential is contingent on the standardization and organization of the data required to train AI models.

“A lot of imaging AI has to do with pattern recognition, which machines are really good at and sort of seeing patterns in data that are not visible to the human eye. Machines can glean from data sets, and these can be used for earlier detection of diseases such as cancer, cardiovascular diseases, and neurological disorders,” he said while speaking at a GovExec event earlier this month.

Farahani further highlighted that integrating AI faces significant challenges, including inconsistent data standards across research institutions, biased data, and the need for training a medical workforce to effectively use AI.

To address these issues, the NHLBI has been actively working on solutions by offering research funding and grants aimed at data curation, preparation, and analytics.