Добірка наукової літератури з теми "Biomedical summarization"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Biomedical summarization".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Biomedical summarization"
Chaves, Andrea, Cyrille Kesiku, and Begonya Garcia-Zapirain. "Automatic Text Summarization of Biomedical Text Data: A Systematic Review." Information 13, no. 8 (August 19, 2022): 393. http://dx.doi.org/10.3390/info13080393.
Повний текст джерелаByrnes, Patrick D., and William Evan Higgins. "Efficient Bronchoscopic Video Summarization." IEEE Transactions on Biomedical Engineering 66, no. 3 (March 2019): 848–63. http://dx.doi.org/10.1109/tbme.2018.2859322.
Повний текст джерелаGuo, Yue, Wei Qiu, Yizhong Wang, and Trevor Cohen. "Automated Lay Language Summarization of Biomedical Scientific Reviews." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 1 (May 18, 2021): 160–68. http://dx.doi.org/10.1609/aaai.v35i1.16089.
Повний текст джерелаPlaza, Laura, Mark Stevenson, and Alberto Díaz. "Resolving ambiguity in biomedical text to improve summarization." Information Processing & Management 48, no. 4 (July 2012): 755–66. http://dx.doi.org/10.1016/j.ipm.2011.09.005.
Повний текст джерелаShang, Yue, Yanpeng Li, Hongfei Lin, and Zhihao Yang. "Enhancing Biomedical Text Summarization Using Semantic Relation Extraction." PLoS ONE 6, no. 8 (August 26, 2011): e23862. http://dx.doi.org/10.1371/journal.pone.0023862.
Повний текст джерелаSaini, Naveen, Sriparna Saha, Pushpak Bhattacharyya, and Himanshu Tuteja. "Textual Entailment--Based Figure Summarization for Biomedical Articles." ACM Transactions on Multimedia Computing, Communications, and Applications 16, no. 1s (April 28, 2020): 1–24. http://dx.doi.org/10.1145/3357334.
Повний текст джерелаDavoodijam, Ensieh, Nasser Ghadiri, Maryam Lotfi Shahreza, and Fabio Rinaldi. "MultiGBS: A multi-layer graph approach to biomedical summarization." Journal of Biomedical Informatics 116 (April 2021): 103706. http://dx.doi.org/10.1016/j.jbi.2021.103706.
Повний текст джерелаDu, Yongping, Qingxiao Li, Lulin Wang, and Yanqing He. "Biomedical-domain pre-trained language model for extractive summarization." Knowledge-Based Systems 199 (July 2020): 105964. http://dx.doi.org/10.1016/j.knosys.2020.105964.
Повний текст джерелаWu, Xiaofang, Zhihao Yang, ZhiHeng Li, Hongfei Lin, and Jian Wang. "Disease Related Knowledge Summarization Based on Deep Graph Search." BioMed Research International 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/428195.
Повний текст джерелаS. Almasoud, Ahmed, Siwar Ben Haj Hassine, Fahd N. Al-Wesabi, Mohamed K. Nour, Anwer Mustafa Hilal, Mesfer Al Duhayyim, Manar Ahmed Hamza, and Abdelwahed Motwakel. "Automated Multi-Document Biomedical Text Summarization Using Deep Learning Model." Computers, Materials & Continua 71, no. 3 (2022): 5799–815. http://dx.doi.org/10.32604/cmc.2022.024556.
Повний текст джерелаДисертації з теми "Biomedical summarization"
Reeve, Lawrence H. Han Hyoil. "Semantic annotation and summarization of biomedical text /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1779.
Повний текст джерелаJaykumar, Nishita. "ResQu: A Framework for Automatic Evaluation of Knowledge-Driven Automatic Summarization." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464628801.
Повний текст джерелаTsatsaronis, George. "An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-202687.
Повний текст джерелаTsatsaronis, George. "An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition." BioMed Central, 2015. https://tud.qucosa.de/id/qucosa%3A29496.
Повний текст джерелаHeng-HuiLiu and 劉恒惠. "Intelligent Biomedical Information Summarization for Omic Study." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/14042056071648837233.
Повний текст джерелаGan, Sheng-Xuan, and 甘昇玄. "A Summarization System for Gene Relations in Biomedical Literatures." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/55977456912415319605.
Повний текст джерела國立成功大學
資訊工程學系碩博士班
92
After creating thirty hundred million DNA sequences’ database by biologists, it needs the high speed process to analyze the vast amounts of data . This paper proposes an summarization system which summarizes a query gene’s related information in biomedical literatures. This system combines three techniques :data mining methodology, natural language processing , finite state machine and consists of three process steps. First ,utilize the author’s writing habits in biomedical literatures and data mining method to extract the candidate related genes , functions and diseases. Second , tag the part-of-speech of sentences’ tokens and simplify the sentence pattern. Third , use finite state machine to extract summary sentences that describe the relation between the query gene and other genes, functions or diseases. Finally , the summary information is integrated to : 1. Information about related genes. 2.Information about related functions. 3. Information about related diseases.This system provides information to help researches about biological pathway ,protein-protein interaction , human cancer gene and gene’s function and increase the process of medical research.
Shang, Tsung-Cheng, and 尚宗承. "Applying Summarization System and Information Distance Method to Biomedical Question Answering System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/76259362842150385968.
Повний текст джерела國立臺灣師範大學
資訊工程學系
102
The study takes Alzheimer’s disease as a subject to implement a biomedical question answering system. The purpose in the thesis is to employ both the properties of a summarization system and an information distance method to the question answering system. The machine learning techniques are also applied, attempting to find out a correct answer from the related literature and background knowledge. The test data is composed of four sets of test documents. Each set includes one document, ten questions and five answer options per question. For each question, there is only one correct answer from the multiple choices. The study also utilizes the background collections from the articles of Medical Literature Analysis and Retrieval System Online, called Medline, and Massachusetts Alzheimer’s Disease Research Center. In the thesis, several different approaches are adopted towards developing an effective question answering system. The first approach is related to methods used in the study of Hou and Tsai in 2014.In this study, the previous approach is extended using the summarization technique to obtain the important information. The second approach is related to the concept of the information distance. The thesis proposes that the information distance between the question and the corresponding correct answer must be smaller than the distances between the question and the other incorrect answers. Furthermore, the concept of the information distance is adapted to fit the characteristics of QA4MRE. Besides, two other techniques, TFIDF computation and the query expansion, are also used in the second approach. Finally, from the experiment of the first approach, it shows that the relevance between the literatures in background knowledge and the question in the test set is not high enough. We observe that, if we make a summary of literatures in background knowledge that may include too many noises among, we can effectively capture the important information needed. From the experiment by the second method, we observe that, if we increase the number of “Question Focus,” we can effectively improve the accuracy of the system. In summary, both summarization and information distance methods are applied to the biomedical question answering system in the study. The experiments show that summarizing the literatures in background knowledge and applying the information distance method can yield good results.
Частини книг з теми "Biomedical summarization"
Rouane, Oussama, Hacene Belhadef, and Mustapha Bouakkaz. "Word Embedding-Based Biomedical Text Summarization." In Advances in Intelligent Systems and Computing, 288–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33582-3_28.
Повний текст джерелаShi, Zhongmin, Gabor Melli, Yang Wang, Yudong Liu, Baohua Gu, Mehdi M. Kashani, Anoop Sarkar, and Fred Popowich. "Question Answering Summarization of Multiple Biomedical Documents." In Advances in Artificial Intelligence, 284–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72665-4_25.
Повний текст джерелаKaykobad Reza, Md, Rifat Rubayatul Islam, Sadik Siddique, Md Mostofa Akbar, and M. Sohel Rahman. "Automatic Summarization of Scientific Articles from Biomedical Domain." In Proceedings of International Joint Conference on Computational Intelligence, 591–602. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3607-6_47.
Повний текст джерелаGupta, Supriya, Aakanksha Sharaff, and Naresh Kumar Nagwani. "Biomedical Text Summarization: A Graph-Based Ranking Approach." In Advances in Intelligent Systems and Computing, 147–56. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2008-9_14.
Повний текст джерелаNasr Azadani, Mozhgan, and Nasser Ghadiri. "Evaluating Different Similarity Measures for Automatic Biomedical Text Summarization." In Advances in Intelligent Systems and Computing, 305–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76348-4_30.
Повний текст джерелаMallick, Chirantana, and Asit Kumar Das. "Hybridization of Fuzzy Theory and Nature-Inspired Optimization for Medical Report Summarization." In Nature-Inspired Optimization Methodologies in Biomedical and Healthcare, 147–74. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17544-2_7.
Повний текст джерелаYoo, Illhoi, Xiaohua Hu, and Il-Yeol Song. "A Coherent Biomedical Literature Clustering and Summarization Approach Through Ontology-Enriched Graphical Representations." In Data Warehousing and Knowledge Discovery, 374–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11823728_36.
Повний текст джерелаRouane, Oussama, Hacene Belhadef, and Mustapha Bouakkaz. "A New Biomedical Text Summarization Method Based on Sentence Clustering and Frequent Itemsets Mining." In Smart Innovation, Systems and Technologies, 144–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21005-2_14.
Повний текст джерелаGupta, Supriya, Aakanksha Sharaff, and Naresh Kumar Nagwani. "Biomedical Text Summarization Based on the Itemset Mining Approach." In Advances in Data Mining and Database Management, 140–52. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8061-5.ch007.
Повний текст джерелаClevert, Djork-Arné, and Axel Rasche. "The Affymetrix GeneChip® Microarray Platform." In Handbook of Research on Systems Biology Applications in Medicine, 251–61. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-076-9.ch014.
Повний текст джерелаТези доповідей конференцій з теми "Biomedical summarization"
Yoo, Illhoi, Xiaohua Hu, and Il-Yeol Song. "Integrating biomedical literature clustering and summarization approaches using biomedical ontology." In the 1st international workshop. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1183535.1183545.
Повний текст джерелаReeve, Lawrence H., Hyoil Han, Saya V. Nagori, Jonathan C. Yang, Tamara A. Schwimmer, and Ari D. Brooks. "Concept frequency distribution in biomedical text summarization." In the 15th ACM international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1183614.1183701.
Повний текст джерелаRai, Akshara, Suyash Sangwan, Tushar Goel, Ishan Verma, and Lipika Dey. "Query Specific Focused Summarization of Biomedical Journal Articles." In 16th Conference on Computer Science and Intelligence Systems. IEEE, 2021. http://dx.doi.org/10.15439/2021f128.
Повний текст джерелаXie, Tianyi, Yi Zhen, Tianqi Li, Chuqin Li, and Yaorong Ge. "Self-supervised extractive text summarization for biomedical literatures." In 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI). IEEE, 2021. http://dx.doi.org/10.1109/ichi52183.2021.00091.
Повний текст джерелаMorales, Laura Plaza, Alberto Díaz Esteban, and Pablo Gervás. "Concept-graph based biomedical automatic summarization using ontologies." In the 3rd Textgraphs Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2008. http://dx.doi.org/10.3115/1627328.1627336.
Повний текст джерелаFiszman, Marcelo, Thomas C. Rindflesch, and Halil Kilicoglu. "Abstraction summarization for managing the biomedical research literature." In the HLT-NAACL Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1596431.1596442.
Повний текст джерела"A Practical Partial Parser for Biomedical Literature Summarization." In 1st International Workshop on Natural Language Understanding and Cognitive Science. SciTePress - Science and and Technology Publications, 2004. http://dx.doi.org/10.5220/0002678700750085.
Повний текст джерелаChandu, Khyathi, Aakanksha Naik, Aditya Chandrasekar, Zi Yang, Niloy Gupta, and Eric Nyberg. "Tackling Biomedical Text Summarization: OAQA at BioASQ 5B." In BioNLP 2017. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/w17-2307.
Повний текст джерелаYamamoto, Y., and T. Takagi. "A Sentence Classification System for Multi Biomedical Literature Summarization." In 21st International Conference on Data Engineering Workshops (ICDEW'05). IEEE, 2005. http://dx.doi.org/10.1109/icde.2005.170.
Повний текст джерелаMenéndez, Héctor D., Laura Plaza, and David Camacho. "A genetic graph-based clustering approach to biomedical summarization." In the 3rd International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2479787.2479807.
Повний текст джерела