Jump to Content
Shashank Agarwal

Shashank Agarwal

Shashank Agarwal completed his PhD in Medical Informatics from University of Wisconsin-Milwaukee. His research involved Information Extraction from published literature.

Currently, Shashank works in the Google Health division in the Bay Area where he focuses on developing AI and NLP-based solutions to improve physicians' productivity.
Authored Publications
Google Publications
Other Publications
Sort By
  • Title
  • Title, desc
  • Year
  • Year, desc
    Building a Clinically-Focused Problem List From Medical Notes
    Birju Patel
    Cathy Cheung
    Hengrui Liu
    Liwen Xu
    Peter Clardy
    Rachana Fellinger
    LOUHI 2022: The 13th International Workshop on Health Text Mining and Information Analysis (2022)
    Preview abstract Clinical notes often contain vital information not observed in other structured data, but their unstructured nature can lead to critical patient-related information being lost. To make sure this valuable information is utilized for patient care, algorithms that summarize notes into a problem list are often proposed. Focusing on identifying medically-relevant entities in the free-form text, these solutions are often detached from a canonical ontology and do not allow downstream use of the detected text-spans. As a solution, we present here a system for generating a canonical problem list from medical notes, consisting of two major stages. At the first stage, annotation, we use a transformer model to detect all clinical conditions which are mentioned in a single note. These clinical conditions are then grounded to a predefined ontology, and are linked to spans in the text. At the second stage, summarization, we aggregate over the set of clinical conditions detected on all of the patient's note, and produce a concise patient summary that organizes their important conditions. View details
    No Results Found