Abstract

Technological advancements have been transforming healthcare rapidly in the past several years. This has been further catalyzed by the COVID-19 pandemic. Several policy changes have been made by the government with added flexibility to enable remote treatment of patients. COVID-19, its symptoms, and medications are being widely discussed on social media. These discussions are also being analyzed by researchers from various perspectives. Moreover, with the availability of wearable fitness devices, these interactions are not limited to a pandemic but go much further. While medical discussions on public forums were prevalent in the past, their prevalence is now highlighted due to the scale of the pandemic.

To address healthcare consumers, Electronic Health Record have been working to make health data of patients easily available to patients. More recently, are also stepping in. Healthcare providers are also making use of automatic speech recognition (ASR) and natural language understanding to understand doctor-patient conversations and generate medical documentation automatically. Finally, smart speakers are now common in households and users interact with them about personal and public health issues.

While applying NLP to open domain is getting increasingly popular, medical conversations present unique challenges and opportunities for impact. After our successful event last year, we are excited to continue the cross-pollination between NLP researchers and medical practitioners. The goal of this workshop is to discuss state-of-the-art approaches in conversational AI, as well as share insights and challenges when applied in healthcare. This is critical in order to bridge existing gaps between research and real-world product deployments, this will further shed light on future directions.

This will be a one-day workshop including keynotes, spotlight talks, posters, and panel sessions. In keynote talks, senior technical leaders from industry and academia will share insights on the latest developments in the field. The panel discussion will focus on the challenges, common framework for evaluating models across sites and future directions of conversational AI research in the medical domain, bridging the gap in research and industrial practice, as well as audience-suggested topics.