Machine Learning in Healthcare: 5 Use Cases that Improve Patient Outcomes

Machine learning is accelerating the pace of scientific discovery across fields, and medicine is no exception. From language processing tools that accelerate research to predictive algorithms that alert medical staff of an impending heart attack, machine learning complements human insight and practice across medical disciplines. However, with all the "solutionism" around AI and machine learning technologies, healthcare providers are understandably cautious about how it will really help patients and bring a return on investment. Many AI solutions on the market for healthcare purposes are tailored to solve a very specific problem, such as identifying the risk of developing sepsis or diagnosing breast cancer. These out-of-the-box AI solutions make it difficult or impossible for companies to customize their models and get the most out of their investment. Open-source data science allows healthcare firms to adapt models to address a variety of challenges using the latest machine learning technologies, such as audio and visual data processing.