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Information extraction and summarization from medical documents

Constantine D. Spyropoulos, Vangelis Karkaletsis
2005 Artificial Intelligence in Medicine  
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

Stergos Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos
2005 Artificial Intelligence in Medicine  
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

P. Gayathri, N. Jaisankar
2015 Cybernetics and Information Technologies  
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

P. Gayathri, N. Jaisankar
2016 Indian Journal of Science and Technology  
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

P. Gayathri, N. Jaisankar
2015 Indian Journal of Science and Technology  
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]

Max Savery, Asma Ben Abacha, Soumya Gayen, Dina Demner-Fushman
2020 arXiv   pre-print
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]

Han-Chin Shing, Chaitanya Shivade, Nima Pourdamghani, Feng Nan, Philip Resnik, Douglas Oard, Parminder Bhatia
2021 arXiv   pre-print
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

Mahdi Gholami Mehr
2013 Intelligent Information Management  
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

Yogan Jaya Kumar, Ong Sing Goh, Halizah Basiron, Ngo Hea Choon, Puspalata C Suppiah
2016 Journal of Computer Science  
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

N. Elhadad, M.-Y. Kan, J.L. Klavans, K.R. McKeown
2005 Artificial Intelligence in Medicine  
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

Juan C. Quiroz, Liliana Laranjo, Ahmet Baki Kocaballi, Shlomo Berkovsky, Dana Rezazadegan, Enrico Coiera
2019 npj Digital Medicine  
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

Minsuk Lee, James Cimino, Hai R Zhu, Carl Sable, Vijay Shanker, John Ely, Hong Yu
2006 AMIA Annual Symposium Proceedings  
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

Ahmed Y., Alaa M.
2018 International Journal of Computer Applications  
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  
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

Ozge Yeloglu, Evangelos Milios, Nur Zincir-Heywood
2011 Proceedings of the 2011 ACM Symposium on Applied Computing - SAC '11  
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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