A Study Suggests Artificial intelligence Can Treat Females With Heart Attacks

Several studies have suggested the prevalence of death due to heart attacks in women is more than in men. The discourse around the causes and consequences of potential treatment gaps has been quiet in discussions. Cardiologists have been concerned about this for decades.

Numerous factors make the risk profile and the clinical picture diverse in women. Heart attack symptoms among women are different than in men. Men experience chest pain spreading to the left arm, while in women, it appears as abdomen discomfort raying to the back or nausea and pukish. Often, these symptoms are misinterpreted by patients and healthcare providers, jeopardising the health of a person. AI-based risk profiling improves individualized care could be efficient and effective.

The study authored by Thomas F. Luscher and his team published in the Lancet journal investigated the role of biological sex in heart attacks in more detail. Thomas Luscher is a professor at the Center for Molecular Cardiology, University of Zurich (UZH). Luscher, in a report said, "Indeed, there are notable differences in the disease phenotype observed in females and males. Our study shows that women and men differ significantly in their risk factor profile at hospital admission," says Luscher. When age differences at admission and existing risk factors such as hypertension and diabetes are disregarded, female heart-attack patients have higher mortality than male patients. "However, when these differences are taken into account statistically, women and men have similar mortality."

Artificial intelligence Can Treat Women Heart Attacks

The researchers analyzed data from 420,781 patients across Europe, who had suffered the most common type of heart attack. The first author Florian A. Wenzl of the Center for Molecular Medicine at UZH established risk models in the study. The risk models that guide current patient management are less accurate in females and favor the undertreatment of female patients. She said that using a machine learning algorithm and the largest datasets in Europe, we develop a novel artificial- intelligence-based risk score that accounts for sex-related differences in the baseline risk profile and improves the mortality predictions in both sexes.

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Further, Wenzl added, "Our study heralds the era of artificial intelligence in the heart attacks treatment. Modern computer algorithms can learn from large data sets to make accurate predictions about the prognosis of individual patients - the key to individualized treatments."

Many biotech companies and researchers believe artificial intelligence and Big Data analytics are the next steps to personalized patient care. Thomas F. Luscher and his team also sees huge potential in the application of artificial intelligence in healthcare management, including for heart diseases. The team also claims implementation of this novel score in treatment algorithms can help reduce sex inequalities and improve the survival of patients with heart attacks.