Neural natural language processing for unstructured data in electronic health records: a review
Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …
Information extraction from electronic medical documents: state of the art and future research directions
MY Landolsi, L Hlaoua, L Ben Romdhane - Knowledge and Information …, 2023 - Springer
In the medical field, a doctor must have a comprehensive knowledge by reading and writing
narrative documents, and he is responsible for every decision he takes for patients …
narrative documents, and he is responsible for every decision he takes for patients …
Natural language processing in oncology: a review
W Yim, M Yetisgen, WP Harris, SW Kwan - JAMA oncology, 2016 - jamanetwork.com
Importance Natural language processing (NLP) has the potential to accelerate translation of
cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of …
cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of …
SECTOR: A neural model for coherent topic segmentation and classification
When searching for information, a human reader first glances over a document, spots
relevant sections, and then focuses on a few sentences for resolving her intention. However …
relevant sections, and then focuses on a few sentences for resolving her intention. However …
Current approaches to identify sections within clinical narratives from electronic health records: a systematic review
A Pomares-Quimbaya, M Kreuzthaler… - BMC medical research …, 2019 - Springer
Background The identification of sections in narrative content of Electronic Health Records
(EHR) has demonstrated to improve the performance of clinical extraction tasks; however …
(EHR) has demonstrated to improve the performance of clinical extraction tasks; however …
[PDF][PDF] Overview of the MEDIQA-Sum Task at ImageCLEF 2023: Summarization and Classification of Doctor-Patient Conversations.
This paper presents the overview of the MEDIQA-Sum task at ImageCLEF 2023. MEDIQA-
Sum 2023 includes three subtasks, in which a doctor-patient dialogue source is given, and …
Sum 2023 includes three subtasks, in which a doctor-patient dialogue source is given, and …
A joint model for document segmentation and segment labeling
Text segmentation aims to uncover latent structure by dividing text from a document into
coherent sections. Where previous work on text segmentation considers the tasks of …
coherent sections. Where previous work on text segmentation considers the tasks of …
Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy
S Chen, M Guevara, N Ramirez, A Murray… - JCO Clinical Cancer …, 2023 - ascopubs.org
PURPOSE Radiotherapy (RT) toxicities can impair survival and quality of life, yet remain
understudied. Real-world evidence holds potential to improve our understanding of …
understudied. Real-world evidence holds potential to improve our understanding of …
A French clinical corpus with comprehensive semantic annotations: development of the Medical Entity and Relation LIMSI annOtated Text corpus (MERLOT)
Quality annotated resources are essential for Natural Language Processing. The objective
of this work is to present a corpus of clinical narratives in French annotated for linguistic …
of this work is to present a corpus of clinical narratives in French annotated for linguistic …
[HTML][HTML] A text processing pipeline to extract recommendations from radiology reports
Communication of follow-up recommendations when abnormalities are identified on
imaging studies is prone to error. The absence of an automated system to identify and track …
imaging studies is prone to error. The absence of an automated system to identify and track …