Katharina Buczek
And it overwhelmingly found that current assessment models are not equipped to properly diagnose women.
“The study shows that established risk models, which guide current patient management, are less accurate in females and favor the undertreatment of female patients,” underscored Florian A. Wenzl, the study’s first author.
The researchers did not stop there, though. They also worked to develop a new machine learning algorithm to diagnose and treat both genders more accurately.
“We were able to develop a novel artificial intelligence-based risk score which accounts for gender-related differences in the baseline risk profile and improves the prediction of mortality in both genders,” Wenzl explained.
Now, the research team hopes this personalized patient care system will help break down gender inequities, refine treatment strategies, and vastly improve heart attack survival rates for people of both genders.
To read the study’s complete findings, visit the link here.
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