NLP for Medical Conversations
ACL Workshop on 10th July 2020 in Seattle, USA
Primary care physicians spend nearly two hours on creating and updating electronic medical/health records (EMR/EHR) for every one hour of direct patient care. Additional administrative and regulatory work has contributed to dissatisfaction, high attrition rates and a burnout rate exceeding 44% among medical practitioners. Recent research has also linked burnout to medical errors, showing doctors who report signs of burnout are twice as likely to have made a medical error. It is imperative to find a solution to minimize causes of such errors, via better tooling and visualization or by providing automated decision support assistants to medical practitioners.
First steps towards introducing automation for clinical documentation have recently emerged. These include approaches from end-to-end clinical documentation to the development of a dialog system with virtual patients for physician training. Commercial products include offerings from large corporations like Microsoft, Nuance, Amazon, and Google to many upcoming startups.
The goal of this workshop is to bring together NLP researchers and medical practitioners, along with experts in machine learning, to discuss the current state-of-the-art approaches, to share their insights and discuss challenges. 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.
- Paper submission deadline:
Monday, April 6th, 2020 11:59 PM ESTMonday, April 13th, 2020 11:59 PM EST
- Review due:
Friday, April 24th, 2020Tuesday, April 28th, 2020
- Author response deadline: Friday, May 1st, 2020
- Acceptance notification: Wednesday, May 8th 2020
- Camera-ready deadline:
Sunday, May 3rd , 2020Tuesday, May 15th 2020
- ACL conference dates: July 5th - July 10th, 2020
- Workshop: 10th July 2020
As vice president of Cerner Intelligence, Dr. Tanuj Gupta leads the product management, data science, and engineering teams for machine learning (ML) and artificial intelligence (AI) in healthcare. The team is actively pursuing predictive and prescriptive intelligence, ambient voice solutions, natural language understanding (NLU), and semantic interoperability.
Dr. Miner is a licensed clinical psychologist and epidemiologist at Stanford University School of Medicine, Dept of Psychiatry and Behavioral Sciences. He uses experimental and observational studies to improve the ability to conversational artificial intelligence to recognize and respond to health issues. Dr. Miner's research has been published in academic outlets such as JAMA, JAMA Internal Medicine, Nature Digital Medicine, and featured in media outlets such as The New York Times, CNN, The Washington Post, The Seattle Times, and ABC.
Dr. Chang is Associate Professor, Department of Obstetrics, Gynecology & Reproductive Sciences, and Internal Medicine at the University of Pittsburgh. Her research investigates female patient communication during patient care. She is also the university's Director of the Clinical Scientist Training Program.
Dr. Bedrick is an Associate Professor of Pediatrics with the School of Medicine at the Oregon Health and Sciences University. His research interests include using NLP for secondary analysis of electronic medical record data and automatic assessment of neuropsychological disorders.
Anitha Kannan is the Head of Machine Learning research at Curai where she works on understanding doctor-patient conversations in healthcare. Curai is building a platform harnessing AI to build products that empower both providers and patients.
Dr. Lipton is an Assistant Professor at Carnegie Mellon University (CMU). His research spans core ML methods and theory, their applications in healthcare and natural language processing, and critical concerns, both about the mode of inquiry itself, and the impact of the technology it produces on social systems.