What if computers could understand or rather read your heart?

–Camelia Bhattacharyya, Amity University Kolkata

Artificial intelligence, a very common term in the 21^st century. It signifies the way in which machines stimulate the intelligence or rather the thinking abilities of humans . Artificial Intelligence runs along with machine learning which is the process of coding to make a computer learn data and use it. After introducing machine learning, the healthcare industry has also undergone a huge lift for prognosis, diagnosis, drug development, and so on. A recent study has demonstrated how aortic hemodynamics and cardiac contractility can be estimated using machine learning without the use of any instruments. 

Cardiovascular problems are right now a major issue to be concerned about since people of all age groups are suffering due to these nowadays. So early and fast diagnosis is crucial. Regression analysis can measure aortic systolic pressure (aSBP), cardiac output (CO), end-systolic elastance (E_es). Whereas the brachial systolic blood pressure (brSBP),  brachial diastolic blood pressure (brDBP), heart rate (HR), and carotid-to-femoral pulse wave velocity (cfPWV) can be used and compared to the aSBP, CO and the E_es in order to track any cardiac problems.

Though these techniques are yet to be implemented, this might work as a miracle in bringing quick diagnosis and healthcare to those in need of it.

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Source: Bikla, V., Papaioannou, T.G., Pagoulatou, S. et al. Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning. Sci Rep 10, 15015 (2020). doi.org//10.1038/s41598-020-72147-8