New Delhi, April 23 (IANS) As cardiovascular disease in women remain underdiagnosed compared to men, new machine learning models that use sex-specific criteria may help overcome this as well as boost treatment outcomes, according to a study. Although anatomical differences exist between male and female hearts as women have smaller hearts with thinner walls, yet, the diagnostic criteria for certain heart diseases have been the same for both. “This means that women’s hearts must increase disproportionately more than men’s before the same risk criteria are met,” argued the researchers in the paper published in the journal Frontiers in Physiology. They said this sex-neutral approach leads to
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