Hybrid Method Incorporating a Rule-Based Approach and Deep Learning for Prescription Error Prediction

Drug Safety ◽  
2021 ◽  
Author(s):  
Seunghee Lee ◽  
Jeongwon Shin ◽  
Hyeon Seong Kim ◽  
Min Je Lee ◽  
Jung Min Yoon ◽  
...  
Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1545
Author(s):  
Chiman Kwan ◽  
Bence Budavari ◽  
Bulent Ayhan

Video activity classification has many applications. It is challenging because of the diverse characteristics of different events. In this paper, we examined different approaches to event classification within a general framework for video activity detection and classification. In our experiments, we focused on event classification in which we explored a deep learning-based approach, a rule-based approach, and a hybrid combination of the previous two approaches. Experimental results using the well-known Video Image Retrieval and Analysis Tool (VIRAT) database showed that the proposed classification approaches within the framework are promising and more research is needed in this area


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Paramita Ray ◽  
Amlan Chakrabarti

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existing machine learning methods for sentiment analysis fail to extract some implicit aspects and might not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rule-based approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-based method and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposed method shows an increment of 7–12% from that of the state-of-the-art methods.


Author(s):  
Padmavathi .S ◽  
M. Chidambaram

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.


2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK

2010 ◽  
Vol 12 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Xueying ZHNAG ◽  
Guonian LV ◽  
Boqiu LI ◽  
Wenjun CHEN

Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.


Author(s):  
Supriya Raheja ◽  
Geetika Munjal ◽  
Jyoti Jangra ◽  
Rakesh Garg

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