9 key thoughts on how machine learning and deep learning will affect healthcare

Artificial intelligence is becoming more important in the healthcare space. Data gathering for machine learning and deep learning capabilities have immense possibilities to improve diagnostics, care pathway creation and reproducibility in surgical procedures to ultimately achieve better clinical outcomes. The technology can also assist physicians with generating reports and administrative responsibilities, giving them more time to spend with patients. Here, nine clinical care and health IT company executives discuss how they expect machine learning and deep learning to improve healthcare in the future. "Deep learning can impact wearables focused on specific conditions, like remote cardiac monitoring, at an individual level by indicating how to personalize algorithms according to one's particular biometric and patient data. The incorporation of machine learning can assist in the interpretations of the analysis of the unstructured data delivered from these medical-grade wearable devices. The initial analysis is typically provided by mathematical algorithms trained to detect anomalies in this data. Machine learning, combined with artificial intelligence, would then seek to perform an interpretation of such a report, just as a physician would, in order to save physician time. Such capabilities effectively reduce physician time, enabling them to focus on the most critical patients and streamline the care process."