Results 221 to 230 of about 6,808 (273)

Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques. [PDF]

Sensors (Basel)
Cabello-Collado C, Rodriguez-Juan J, Ortiz-Perez D, Garcia-Rodriguez J, Tomás D, Vizcaya-Moreno MF.   +5 more
europepmc   +1 more source

Developing and Evaluating Large Language Model-Generated Emergency Medicine Handoff Notes.

JAMA Netw Open
Hartman V, Zhang X, Poddar R, McCarty M, Fortenko A, Sholle E, Sharma R, Campion T, Steel PAD.   +8 more
europepmc   +1 more source

Contextual priority attention enables linear time sequence modeling in transformers. [PDF]

Sci Rep
Khaled KB, Monticolo D.
europepmc   +1 more source

ClinicSum: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations. [PDF]

Proc IEEE Int Conf Big Data
Neupane S, Tripathi H, Mitra S, Bozorgzad S, Mittal S, Rahimi S, Amirlatifi A.   +6 more
europepmc   +1 more source

Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark Study.

JMIR Ment Health
Adhikary PK, Srivastava A, Kumar S, Singh SM, Manuja P, Gopinath JK, Krishnan V, Gupta SK, Deb KS, Chakraborty T.   +9 more
europepmc   +1 more source

Task-Specific Transformer-Based Language Models in Health Care: Scoping Review.

JMIR Med Inform
Cho HN, Jun TJ, Kim YH, Kang H, Ahn I, Gwon H, Kim Y, Seo J, Choi H, Kim M, Han J, Kee G, Park S, Ko S.   +13 more
europepmc   +1 more source

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Graph-based abstractive biomedical text summarization

Journal of Biomedical Informatics, 2022
Summarization is the process of compressing a text to obtain its important informative parts. In recent years, various methods have been presented to extract important parts of textual documents to present them in a summarized form. The first challenge of these methods is to detect the concepts that well convey the main topic of the text and extract ...
Azadeh Givchi, Reza Ramezani, Ahmad Baraani-Dastjerdi   +2 more
openaire   +2 more sources

Hybrid Model For Abstractive Text Summarization

SSRN Electronic Journal, 2021
Text Summarization is a method to reduce a huge text into a meaningful condensed form. Today’s era is technological era. The people are always in the need of instant information in the concise form. As well as World Wide Web has expanded now-a-days so there is tremendous amount of data is created and available online.
Sujata Kolhe, Poonam Patil
openaire   +1 more source

Survey on Abstractive Text Summarization

2018 International Conference on Communication and Signal Processing (ICCSP), 2018
This paper provides a review on some of the significant research work done on abstractive text summarization. The process of generating the summary from one or more text corpus, by keeping the key points in the corpus is called text summarization. The most prominent technique in text summarization is an abstractive and extractive method. The extractive
Nithin Raphal, Hemanta Duwarah, Philemon Daniel   +2 more
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Comparative Study on Abstractive Text Summarization

2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2020
This paper represents a comparative study and gives an overview on some of the great research work done on abstractive text summarization. Getting a gist part from a large text document is known as text summarization. In recent years, text summarization became one of the most interesting and crucial research point in Natural Language Processing(NLP ...
Md Ashraful Islam Talukder, Sheikh Abujar, Abu Kaisar Mohammad Masum, Sharmin Akter, Syed Akhter Hossain   +4 more
openaire   +1 more source