There has been a lot of talk around the applications of machine learning in medicine. But how is machine learning actually helping scientists and clinicians do their jobs? This interesting topic came to us from the Medical Device & Diagnostic Industry (MDDI) in their article, “Transforming Modern Medical Devices with Machine Learning & AI Inference.”
Artificial intelligence (AI) technology adoption is happening in the medical device industry, and it’s not just driving exciting new features and high-end functionalities into the devices themselves. This technology is also enabling manufacturers to reap the rewards from new service models but improve healthcare along the way.
In the clinic, machine learning (a subset of AI) plays a key role in many health-related realms, including the development of new medical procedures, the handling of patient data and records and the treatment of chronic diseases.
Most organizations, including healthcare providers, have little visibility and knowledge of how AI systems make the decisions they do. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. “Explainable AI” is used to describe an AI model, its expected impact and potential biases. Why is this important? Because the results can have an impact on data security or patient safety.
Melody K. Smith
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
