Artificial intelligence (AI) and machine learning (ML) in medical devices is an important part of the healthcare industry with the potential to improve patient care, as well as administrative processes by automating tasks and achieving faster results. According to the latest report by PwC, AI will contribute an additional $15.7 trillion to the world economy by 2030, with the greatest impact being in the field of healthcare. Real-world applications of AI and ML in medical devices include imaging systems used for diagnostic information, smart electrocardiograms estimating the probability of a heart attack, and AI-assisted stethoscopes that patients can use at home.
Artificial Intelligence can be broadly defined as the:
“science and engineering of making intelligent machines, especially intelligent computer programs using models based on statistical analysis of data, expert systems that primarily rely on if-then statements, and machine learning.”
Machine Learning is an:
“artificial intelligence technique that can be used to design and train software algorithms to learn from and act on data, essentially creating adaptive algorithms that have the potential to continuously optimize device performance in real-time to improve patient outcomes.”