Dhiman, Gaurav and Juneja, Sapna and Viriyasitavat, Wattana and Mohafez, Hamidreza and Hadizadeh, Maryam and Islam, Mohammad Aminul and El Bayoumy, Ibrahim and Gulati, Kamal (2022) A novel machine-learning-based hybrid cnn model for tumor identification in medical image processing. Sustainability, 14 (3). ISSN 2071-1050, DOI https://doi.org/10.3390/su14031447.
Full text not available from this repository.Abstract
The popularization of electronic clinical medical records makes it possible to use automated methods to extract high-value information from medical records quickly. As essential medical information, oncology medical events are composed of attributes that describe malignant tumors. In recent years, oncology medicine event extraction has become a research hotspot in academia. Many academic conferences publish it as an evaluation task and provide a series of high-quality annotation data. This article aims at the characteristics of discrete attributes of tumor-related medical events and proposes a medical event. The standard extraction method realizes the combined extraction of the primary tumor site and primary tumor size characteristics, as well as the extraction of tumor metastasis sites. In addition, given the problems of the small number and types of annotation texts for tumor-related medical events, a key-based approach is proposed. A pseudo-data-generation algorithm that randomly replaces information in the whole domain improves the transfer learning ability of the standard extraction method for different types of tumor-related medical event extractions. The proposed method won third place in the clinical medical event extraction and evaluation task of the CCKS2020 electronic medical record. A large number of experiments on the CCKS2020 dataset verify the effectiveness of the proposed method.
| Item Type: | Article |
|---|---|
| Funders: | Malaysian Ministry of Higher Education through FRGS grant [Grant No: FRGS/1/2020/TK0/UM/02/33], Universiti Malaya [Grant No: RU013AC-2021] |
| Uncontrolled Keywords: | Electronic medical records; Medical event extraction; Migration learning; Joint extraction |
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > Q Science (General) T Technology > T Technology (General) |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering Faculty of Sports and Exercise Science (formerly known as Centre for Sports & Exercise Sciences) |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 08 Aug 2022 07:23 |
| Last Modified: | 08 Aug 2022 07:23 |
| URI: | http://eprints.um.edu.my/id/eprint/33398 |
Actions (login required)
 |
View Item |
