Smarter Heart Attack Risk Assessment Through ML

Modern technologies are allowing people and healthcare providers detect heart risks better. 

Healthy Heart|Jan.10, 2023

It is human tendency to be intrigued about the future. Having some idea of what can happen offers the chance to prepare for it. The same principle when applied to our health can help us take better care of ourselves, especially when it comes to conditions like cardiovascular diseases (CVDs) which have subtle symptoms that can get easily missed . What if technology could help us asses any potential risk to our heart health through precise, relevant, and visible data?

Our bodies can sometimes deceive us; we may appear completely healthy on the surface but can have an underlying health risk and not know about it. Being able to notice and understand even mild symptoms, through modern medical technologies, can help mitigate heart health risks if cautioned in time.

Better diagnosis, optimized treatment

Today, there is an extraordinary volume of clinical and biological data available – like, static data from patient records, reports, biomedical imaging, and dynamic data from bedside monitors or remote wearable sensors, etc. If read and interpreted correctly, this data can play a critical role in building our capability for the predictive analysis of heart diseases. Technologies like artificial intelligence (AI) and machine learning (ML) can be great tools to interpret health data from multiple sources and help find unseen patterns. With the use of machine learning (ML), these solutions can be further refined for better outcomes.

With the help of ML algorithms, doctors and scientists can derive deeper insights from heart disease screening data and identify previously unseen patterns, markers, and risk factors associated with cardiovascular diseases. For instance, combining patient information such as age and gender with the amount of proteins found in their hearts can improve healthcare providers’ diagnosis. With more insights at hand, healthcare practitioners have a better chance at identifying heart disease risks early and with greater accuracy, ultimately saving more lives.

Transforming cardiovascular care with AI, ML, and big data

Globally, out-of-hospital heart attacks are extremely common, increasing the significance of accurate risk prediction. Using blood samples to run certain tests (like the high-sensitivity troponin I-test) and analyzing the results using AI and ML can prove quite beneficial when attempting to predict the possibility of heart attacks. Imaging assets like AI-guided ECGs can spot faulty heart rhythms even before a person can experience any symptoms. ML techniques are most extensively tested in cardiovascular imaging and have tremendous immediate potential. Most importantly, AI/ML-based predictive analysis improves shared and informed decision-making by doctors and their patients and helps make personalized healthcare a reality.

Technology – a crystal ball for the healthcare sector 

 AI and ML when combined have the potential to improve the understanding of our health, how bodies behave, and how heart disease can be better managed. One of the most significant developments it can lead to is informed risk assessment through existing and new data. It offers a more holistic understanding of patient health for doctors and thereby, provides the opportunity for more personalized care, giving people the ability to manage their health better and live healthier lives.

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