Identification of Drug-Drug Interactions Using OCR

被引:0
作者
Alrehily, Enas Saleem [1 ]
Alhejaili, Rawan Fahad [1 ]
Albeladi, Dalal Rasheed [1 ]
Syed, Liyakathunisa [1 ]
机构
[1] Taibah Univ, Coll Comp Sci & Engn, Medinah, Saudi Arabia
来源
IOT TECHNOLOGIES FOR HEALTH CARE, HEALTHYIOT 2021 | 2022年 / 432卷
关键词
OCR; Drug-drug interactions; Text detection; Drug label;
D O I
10.1007/978-3-030-99197-5_11
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Text detection and recognition in natural images have recently gained the attention of many researchers. It plays a significant role in different applications such as labels package identifications, and many blind assistance applications. OCR is widely used for this purpose. Precisely, for the drug label identification. It can be used to detect the Drug-Drug Interaction (DDI) which considers as one of the challenging tasks in public health safety. In this research, OCR is used to detect and extract the drug name from the drug boxes. Then the extracted drug name is used as input for the DDI identification process. The results of the proposed system are promising.
引用
收藏
页码:125 / 135
页数:11
相关论文
共 17 条
[1]  
[Anonymous], FOOT ULCERS DIABETIC
[2]  
Carneiro, 2019, ARXIV PREPRINT ARXIV
[3]   A Deep Learning-Based Intelligent Medicine Recognition System for Chronic Patients [J].
Chang, Wan-Jung ;
Chen, Liang-Bi ;
Hsu, Chia-Hao ;
Lin, Cheng-Pei ;
Yang, Tzu-Chin .
IEEE ACCESS, 2019, 7 :44441-44458
[4]  
Demner-Fushman D., 2019, P TEXT AN C TAC 2018
[5]  
Dhande P. S., 2017, INT C COMP COMM CONT, P1, DOI 10.1109/ICCUBEA.2017.8463842
[6]  
Kulkarni C.R., 2017, Int. Res. J. Eng. Technol. (IRJET), V4, P179
[7]   DLI-IT: a deep learning approach to drug label identification through image and text embedding [J].
Liu, Xiangwen ;
Meehan, Joe ;
Tong, Weida ;
Wu, Leihong ;
Xu, Xiaowei ;
Xu, Joshua .
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (01)
[8]  
MathWorks, REC TEXT US OPT CHAR
[9]  
Nadarajan A.S, 2018, INT J ENG DEV RES, V6, P60
[10]  
National Library of Medicine-National Institutes of Health, NAT LIB MED NAT I HL