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 …
Region-based convolutional neural network for segmenting text in epigraphical images
P Preethi, HR Mamatha - Artificial Intelligence and …, 2023 - ojs.bonviewpress.com
Region-Based Convolutional Neural Network for Segmenting Text in Epigraphical Images Page
1 Received: 1 July 2022 | Revised: 31 August 2022 | Accepted: 6 September 2022 | Published …
1 Received: 1 July 2022 | Revised: 31 August 2022 | Accepted: 6 September 2022 | Published …
Text segmentation by cross segment attention
Document and discourse segmentation are two fundamental NLP tasks pertaining to
breaking up text into constituents, which are commonly used to help downstream tasks such …
breaking up text into constituents, which are commonly used to help downstream tasks such …
Improving unsupervised dialogue topic segmentation with utterance-pair coherence scoring
L Xing, G Carenini - arXiv preprint arXiv:2106.06719, 2021 - arxiv.org
Dialogue topic segmentation is critical in several dialogue modeling problems. However,
popular unsupervised approaches only exploit surface features in assessing topical …
popular unsupervised approaches only exploit surface features in assessing topical …
A two-stage transformer-based approach for variable-length abstractive summarization
This study proposes a two-stage method for variable-length abstractive summarization. This
is an improvement over previous models, in that the proposed approach can simultaneously …
is an improvement over previous models, in that the proposed approach can simultaneously …
Unsupervised topic segmentation of meetings with bert embeddings
A Solbiati, K Heffernan, G Damaskinos… - arXiv preprint arXiv …, 2021 - arxiv.org
Topic segmentation of meetings is the task of dividing multi-person meeting transcripts into
topic blocks. Supervised approaches to the problem have proven intractable due to the …
topic blocks. Supervised approaches to the problem have proven intractable due to the …
Machine learning-based automatic detection of central sleep apnea events from a pressure sensitive mat
Polysomnography (PSG) is the standard test for diagnosing sleep apnea. However, the
approach is obtrusive, time-consuming, and with limited access for patients in need of sleep …
approach is obtrusive, time-consuming, and with limited access for patients in need of sleep …
Chapter captor: Text segmentation in novels
Books are typically segmented into chapters and sections, representing coherent
subnarratives and topics. We investigate the task of predicting chapter boundaries, as a …
subnarratives and topics. We investigate the task of predicting chapter boundaries, as a …
Improving context modeling in neural topic segmentation
Topic segmentation is critical in key NLP tasks and recent works favor highly effective neural
supervised approaches. However, current neural solutions are arguably limited in how they …
supervised approaches. However, current neural solutions are arguably limited in how they …
Improving long document topic segmentation models with enhanced coherence modeling
Topic segmentation is critical for obtaining structured long documents and improving
downstream tasks like information retrieval. Due to its ability of automatically exploring clues …
downstream tasks like information retrieval. Due to its ability of automatically exploring clues …