Clinicians spend a large amount of time on clinical documentation of patient encounters,
often impacting quality of care and clinician satisfaction, and causing physician burnout …

Following each patient visit, physicians draft long semi-structured clinical summaries called
SOAP notes. While invaluable to clinicians and researchers, creating digital SOAP notes is …

Due to the lack of publicly available resources, conversation summarization has received far
less attention than text summarization. As the purpose of conversations is to exchange …

Summarization is an important natural language processing (NLP) task in identifying key
information from text. For conversations, the summarization systems need to extract salient …

Artificial Intelligence (AI) is playing a major role in medical education, diagnosis, and
outbreak detection through Natural Language Processing (NLP), machine learning models …

Abstractive conversation summarization has received growing attention while most current
state-of-the-art summarization models heavily rely on human-annotated summaries. To …

Deep learning (DL) has substantially enhanced natural language processing (NLP) in
healthcare research. However, the increasing complexity of DL-based NLP necessitates …

Abstractive dialogue summarization has received increasing attention recently. Despite the
fact that most of the current dialogue summarization systems are trained to maximize the …

Summaries of medical text shall be faithful by being consistent and factual with source
inputs, which is an important but understudied topic for safety and efficiency in healthcare. In …

Objective We developed a digital scribe for automatic medical documentation by utilizing
elements of patient-centered communication. Excessive time spent on medical …