AI in Healthcare and Medicine: A Systematic Literature Review and Reappraisal

Healthcare and medicine are on the verge of undergoing an artificial intelligence-powered transformation. The expected benefits range from improved patient safety, new treatment options, precise medical diagnoses, personalized health monitoring, and a reduction in healthcare costs. With large amounts of existing data stored in electronic health records (EHRs) and advanced multi-sensor health tracking devices generating new data, artificial intelligence (AI) will be able to generate insights that aid physicians in providing high-quality medical care. Due to AI becoming a recent mainstream topic, which is advancing rapidly, understanding the potential positive impacts, negative impacts, and current research landscape is important in guiding available resources. This document is a systematic literature review of our topic choice using current literature and emergent trends. The review was conducted using several tools like VOSviewer, Harzing’s Publish or Perish, CiteSpace, and NVivo, as well as multiple databases like Scite.ai, Scopus, Web of Science, Google Scholar, Dimensions.ai, and Springer. Bibliometric, co-citation, citation burst, and content analyses conducted with use of these databases and tools to demonstrate the connections among AI and healthcare and medicine. The results of the analyses indicate that AI in healthcare and medicine is an emerging topic of interest and aided in the identification of articles revealing five key subtopics including disease diagnosis using medical imaging, drug discovery and re-purposing, wearable devices, sensors, and edge computing. Overall, the results of this study indicate that the ethical and responsible implementation of AI in healthcare will transform the delivery of patient care.