The seminar is part of the “91248 - FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE AND KNOWLEDGE REPRESENTATION” course.
Abstract: The "AI revolution" is lavished with accolades and showered with concerns. We focus specifically on medical applications that rely on search or recommendation technology. Relying on these technologies, we alleviate the ever-growing shortage of medical care personnel. Specifically, patient interactions are simplified by conversational agents, medical triage is accomplished by self-administered surrogates, early-onset of mental health conditions are detected through opt-in monitoring agents, and treatment suggestions are generated and evaluated via retrieval and mining applications. These are just some examples where search and related technologies are reshaping medical practice. Currently or soon to be deployed systems are described. "In progress" efforts are likewise highlighted. While some of the described systems rely on recent technology advances, others are simply based on "bread and butter" approaches, reminding us that "new and improved" is not always needed, and at times, is overkill and needlessly costly. We conclude with some observations.
Bio: Ophir Frieder focuses on scalable information processing systems with particular emphasis on health informatics. He is a member of the computer science faculty at Georgetown University and the biostatistics, bioinformatics and biomathematics faculty at the Georgetown University Medical Center. https://scholar.google.com/citations?user=uUXCSMkAAAAJ&hl=en