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Information extraction and summarization from medical documents
2005
Artificial Intelligence in Medicine
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They would also like to acknowledge the excellent work performed by the 30 reviewers from 13 different countries who were involved in the review process. ...
Concluding remarks There is a constantly growing interest on the research field of information extraction and summarization from medical documents. ...
medical document types and summarization applications. ...
doi:10.1016/j.artmed.2004.08.002
pmid:15811779
fatcat:siqzvxotlzdznob4oktyiuqhkm
Summarization from medical documents: a survey
2005
Artificial Intelligence in Medicine
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Discussion and conclusions: The paper discusses thoroughly the promising paths for future research in medical documents summarization. ...
Objective: The aim of this paper is to survey the recent work in medical documents summarization. ...
Spyropoulos and Dr. George Paliouras, for their helpful and constructive comments. Many thanks also to Ms. Eleni Kapelou and Ms. Irene Doura for checking the use of English. ...
doi:10.1016/j.artmed.2004.07.017
pmid:15811783
fatcat:n7u6ji5t2rgkvjktacjf4rdire
Towards an Efficient Approach for Automatic Medical Document Summarization
2015
Cybernetics and Information Technologies
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Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document summarization approach. ...
A sentence ranking method is used to extract the important sentences. The existing summarizers are used for performance analysis. ...
In this scenario, medical professionals and researchers demand relevant medical information from a healthcare information system. ...
doi:10.1515/cait-2015-0056
fatcat:7daxnewbxrettotlqujmoav2au
A Study on Some Tasks, Corpus and Resources of Medical Information Retrieval
2016
Indian Journal of Science and Technology
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An extractive informative generic mono-lingual single-document summarizer is used to produce medical domain-specific summary. ...
In the medical domain, richest and most used source of information is MEDLINE. ...
Various categories and types of summarization methods
Category Type Description
Nature of text obtained Extractive Summary is formed by mining key sentences from original document. ...
doi:10.17485/ijst/2016/v9i25/86655
fatcat:ghsig6x4zvgrnbf7xa662hbsoe
An Efficient Medical Document Summarization using Sentence Feature Extraction and Ranking
2015
Indian Journal of Science and Technology
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Summary produced by any summarizer can be highly informative if and only if it contains dissimilar sentences. ...
The evaluation is done by using traditional metrics such as precision and recall and ROUGE. Not all medical documents come with an author written abstract or summary. ...
The extractive informative single document summarization approach has been used in which the important step is to identify summary worthy sentences from the source document and at the same time reducing ...
doi:10.17485/ijst/2015/v8i33/71257
fatcat:x55sywqrqfhspfkpbmfrcug4ie
Question-Driven Summarization of Answers to Consumer Health Questions
[article]
2020
arXiv
pre-print
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For example, in the medical domain, recent developments in deep learning approaches to automatic summarization have the potential to make health information more easily accessible to patients and consumers ...
This dataset can be used to evaluate single or multi-document summaries generated by algorithms using extractive or abstractive approaches. ...
A.B-A authored the MEDIQA data used as the backbone for the collection presented here, as well as the MedInfo data used for training, provided guidance on their use, developed the summarization interface ...
arXiv:2005.09067v2
fatcat:ouwgy6mxrfdqjplqcsbi3x62wq
Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes
[article]
2021
arXiv
pre-print
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The records of a clinical encounter can be extensive and complex, thus placing a premium on tools that can extract and summarize relevant information. ...
Summaries in this setting need to be faithful, traceable, and scale to multiple long documents, motivating the use of extract-then-abstract summarization cascades. ...
By building a system to extract and compose these medical sections from prior clinical notes in the same encounter, we can summarize the information in a format clinicians are already trained to read and ...
arXiv:2104.13498v1
fatcat:mkpw3njbvfcabmsbh2qq5rrl7e
Using AdaBoost Meta-Learning Algorithm for Medical News Multi-Document Summarization
2013
Intelligent Information Management
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Since the number and variety of online medical news make them difficult for experts in the medical field to read all of the medical news, an automatic multi-document summarization can be useful for easy ...
In this paper, we discuss about multi-document summarization that differs from the single one in which the issues of compression, speed, redundancy and passage selection are critical in the formation of ...
In this paper, we present a machine learning based model for a sentence extraction based, Multi document, and informative text summarization in the medical domain (This work is an improvement of the study ...
doi:10.4236/iim.2013.56020
fatcat:ewylrtz62jbmrg7mhl2n7dtvwy
A Review on Automatic Text Summarization Approaches
2016
Journal of Computer Science
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Various techniques have been successfully used to extract the important contents from text document to represent document summary. ...
Furthermore, this paper also reviews the significant efforts which have been put in studies concerning sentence extraction, domain specific summarization and multi document summarization and provides the ...
Ethics This article is original and contains unpublished material. The corresponding author confirms that all of the other authors have read and approved the manuscript and no ethical issues involved. ...
doi:10.3844/jcssp.2016.178.190
fatcat:rlydvxlgljgajacrg2be7sckdm
Customization in a unified framework for summarizing medical literature
2005
Artificial Intelligence in Medicine
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Results: The resulting summaries combine both machine-generated text and extracted text that comes from multiple input documents. ...
Methods and Material: Our summarizer employs a unified user model to create a tailored summary of relevant documents for either a physician or lay person. ...
To address this need, we plan to design a new summarization module to extract answers from medical textbooks, which will complement the TAS and Centrifuser components. ...
doi:10.1016/j.artmed.2004.07.018
pmid:15811784
fatcat:xsykbwtsynf55bzlc4jrt6afbe
Challenges of developing a digital scribe to reduce clinical documentation burden
2019
npj Digital Medicine
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using speech recognition, inducing topic structure from conversation data, extracting medical concepts, generating clinically meaningful summaries of conversations, and obtaining clinical data for AI and ...
by clinicians or medical scribes. ...
, and (3) extract salient information from the text and summarize the information (Fig. 1) . ...
doi:10.1038/s41746-019-0190-1
pmid:31799422
pmcid:PMC6874666
fatcat:y7owfblwlvc2dowldwf4c6pqbe
Beyond information retrieval--medical question answering
2006
AMIA Annual Symposium Proceedings
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Although our long term goal is to enable MedQA to answer all types of medical questions, currently, we implemented MedQA to integrate information retrieval, extraction, and summarization techniques to ...
The authors address physicians' information needs and described the design, implementation, and evaluation of the medical question answering system (MedQA). ...
Semantic information plays an important role for both answer extraction and summarization and they are not captured in current MedQA implementation. ...
pmid:17238385
pmcid:PMC1839371
fatcat:4wfvs42idnf4xpgedvlarovgpq
Template based Medical Reports Summarization
2018
International Journal of Computer Applications
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The information extracted from medical reports is very useful to medical staff to detect hidden relations between medical information, and making decisions that will improve the medical service for patients ...
Medical information extraction is one of the important topics that aim to identify medical information and detect hidden relations. ...
The best results have been noted in the Department of Neurology and followed by thoracic section. Also, the best ...
doi:10.5120/ijca2018916301
fatcat:sw67zkdq65atjhcfvzjpgukgru
Utilization of Summarization Algorithms for a Better Understanding of Clustered Medical Documents
2019
International Journal of Engineering and Advanced Technology
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Medical documents contain rich information about the diseases, medication, symptoms and precautions. ...
Extraction of useful information from large volumes of medical documents that are generated by electronic health record systems is a complex task as they are unstructured or semi-structured. ...
He has received several awards for his excellence in Teaching, Research and Administration like "State Best Teacher award", "Best Researcher award", "Distinguished Principal award" from the Government ...
doi:10.35940/ijeat.b4409.129219
fatcat:yomegowfofc7tpljzp5nekjjk4
Multi-document summarization of scientific corpora
2011
Proceedings of the 2011 ACM Symposium on Applied Computing - SAC '11
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MEAD with built-in default vocabulary, MEAD with corpus specific vocabulary extracted by Keyphrase Extraction Algorithm (KEA), LexRank (a state-of-the-art summarization algorithm based on random walk) ...
On the other hand, visual inspection shows us that current content evaluation methods, which use only the gold-standard keyterm information, are not intuitive and focus must turn into better evaluation ...
As seen in Table 5 , MEAD Original and LexRank tend to extract long sentences from the beginning of the documents, which are the introduction sentences. ...
doi:10.1145/1982185.1982243
dblp:conf/sac/YelogluMZ11
fatcat:zklj7gjueffdtgrgughbx34e54
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