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.
Disclaimer: This publication/article/editorial is meant for awareness/educational purposes and does not constitute or imply an endorsement, sponsorship or recommendation of any products. Please consult your doctor/healthcare practitioner before starting any diet, medication or exercise.
FOLLOW ABBOTT