Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Deshpande, Leena
- An Approach for Auto-Generating Solution to User-Generated Medical Content Using Deep Learning Techniques
Abstract Views :452 |
PDF Views:2
Authors
Affiliations
1 Department of Computer Engineering, Vishwakarma Institute of Information Technology, IN
1 Department of Computer Engineering, Vishwakarma Institute of Information Technology, IN
Source
ICTACT Journal on Soft Computing, Vol 8, No 3 (2018), Pagination: 1668-1673Abstract
One of many things humans are obsessive about is health. Presently, when faced with a health-related issue one goes to the web first, to find closure to his/her problem. The community Question Answering (cQA) forum allows people to pose their query and/or discuss it. Due to alike or unique nature of the health query it may go unanswered. Many a time the answers provided are ill-founded, leaving the user discontent. This indicates that the process is dependent on supplementary users or experts, in relation to their ability and/or the time taken to answer the question. Hence, the need to create an answer predictor which provides instant and better-quality result. We, therefore propose a novel scheme where deep learning is used to produce appropriate answer to the given health query. Both historical data i.e. cQA and general medical data are used to form a powerful Knowledge Base (KB), to assist the health predictor.Keywords
Community Question Answering, Deep Learning, Health- Related Issue.
References
- X.Y. Peng, Y. Chen and Z.W. Huang, “A Chinese Question Answering System using Web Service on Restricted Domainâ€, Proceedings of International Conference on Artificial Intelligence and Computational Intelligence, pp. 350-353, 2010.
- H. Zhang, L. Zhu, S. Xu and W. Li, “Xml-Based Document Retrieval in Chinese Diseases Question Answering Systemâ€, Mobile, Ubiquitous, and Intelligent Computing, Vol. 274, pp. 211-217. 2014.
- Kishore Papineni, Salim Roukos, Todd Ward and Wei-Jing Zhu, “BLEU: A Method for Automatic Evaluation of Machine Translationâ€, Proceedings of 40th Annual Meeting of the Association for Computational Linguistics, pp. 311318, 2002.
- Kazuma Hashimoto et al., “A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasksâ€, Proceedings of International Conference on Empirical Methods in Natural Language Processing, pp. 1-7, 2017.
- Trevor Hastie, Robert Tibshirani and Jerome Friedman, “The Elements of Statistical Learning: Data Mining, Inference, and Predictionâ€, Springer, 2001.
- Liqiang Nie, Xiaochi Wei, Dongxiang Zhang, Xiang Wang, Zhipeng Gao and Yi Yang. “Data-Driven Answer Selection in Community QA Systemsâ€, IEEE Transactions on Knowledge and Data Engineering, Vol. 29, No. 6, pp. 413-421, 2017.
- Zongcheng Ji, Zhengdong Lu and Hang Li, “An Information Retrieval Approach to Short Text Conversationâ€, Proceedings of International Conference on Computation and Language, pp. 23-27, 2014.
- Lifeng Shang, Zhengdong Lu and Hang Li, “Neural Responding Machine for Short-Text Conversationâ€, Proceedings of 53rd Annual Meeting of the Association for Computational Linguistics, pp. 1577-1586, 2015.
- D.A. Davis, N.V. Chawla, N. Blumm, N. Christakis and A.L. Barabasi, “Predicting Individual Disease Risk based on Medical Historyâ€, Proceedings of International Conference on Information and Knowledge Management, pp. 773-778, 2008.
- S. Doan and H. Xu, “Recognizing Medication Related Entities in Hospital Discharge Summaries using Support Vector Machineâ€, Proceedings of International Conference on Computational Linguistics, pp. 330-337, 2010.
- I. Batal, L. Sacchi, R. Bellazzi and M. Hauskrecht, “A Temporal Abstraction Framework for Classifying Clinical Temporal Dataâ€, Proceedings of American Medical Informatics Association, pp. 227-234, 2008.
- K. Latha and R. Rajaram, “Improvisation of Seeker Satisfaction in Yahoo! Community Question Answering Portalâ€, ICTACT Journal on Soft Computing, Vol. 1, No. 3 pp. 152-162, 2011.
- R. Fakoor, F. Ladhak, A. Nazi and M. Huber, “Using Deep Learning to Enhance Cancer Diagnosis and Classificationâ€, Proceedings of International Conference on Machine Learning, pp. 291-297, 2013.
- M. Shouman, T. Turner and R. Stocker, “Using Decision Tree for Diagnosing Heart Disease Patientsâ€, Proceedings of 9th Australasian Data Mining Conference, pp. 336-343, 2011.
- Y. Zhang and B. Liu, “Semantic Text Classification of Disease Reportingâ€, Proceedings of the International ACM SIGIR Conference, pp. 43-49, 2007.
- J. Zhou, L. Yuan, J. Liu and J. Ye, “A Multi-Task Learning Formulation for Predicting Disease Progressionâ€, Proceedings of ACM International Conference on Knowledge Discovery and Data Mining, pp. 881-885, 2011.
- B. Koopman, P. Bruza, L. Sitbon and M. Lawley, “Evaluating Medical Information Retrievalâ€, Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 123-128, 2011.
- P. Sondhi, J. Sun, H. Tong and C. Zhai, “Sympgraph: A Framework for Mining Clinical Notes through Symptom Relation Graphsâ€, Proceedings of International ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 21-24, 2012.
- S. Ghumbre, C. Patil and A. Ghatol, “Heart Disease Diagnosis using Support Vector Machineâ€, Proceedings of International Conference on Computer Science and Information Technology, pp. 12-16, 2011.
- Sebastian Basterrech, Jan Janousek and Vaclav Snasel, “A Performance Study of Random Neural Network as Supervised Learning Tool using CUDAâ€, Journal of Internet Technology, Vol. 17, No. 4, pp. 771-778, 2016.
- S.H. Yang, S.P. Crain and H. Zha, “Bridging the Language Gap: Topic Adaptation for Documents with Different Technicalityâ€, Proceedings of 14th International Conference on Artificial Intelligence and Statistics, pp. 91-95, 2011.
- Alan Ritter, Colin Cherry and William B. Dolan, “DataDriven Response Generation in Social Mediaâ€, Proceedings of Conference on Empirical Methods in Natural Language Processing, pp. 141-146, 2011.
- F. Wang, N. Lee, J. Hu, J. Sun, S. Ebadollahi and A. Laine, “A Framework for Mining Signatures from Event Sequences and its Applications in Healthcare Dataâ€, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 2, pp. 272-285, 2013.
- F. Wang, N. Lee, J. Hu, J. Sun and S. Ebadollahi, “Towards Heterogeneous Temporal Clinical Event Pattern Discovery: A Convolutional Approachâ€, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp.178-183, 2012.
- A. Khosla, Y. Cao, C. C.Y. Lin, H.K. Chiu, J. Hu and H. Lee,†An Integrated Machine Learning Approach to Stroke Predictionâ€, Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 30-34, 2010.
- K. Karpagam and A. Saradha, “An Intelligent Conversation Agent for Health Care Domainâ€, ICTACT Journal on Soft Computing, Vol. 4, No. 3, pp. 772-776, 2014.