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Extraction of Aspects from Drug Reviews Using Probabilistic Aspect Mining Model
2015
International Journal of Science and Research (IJSR)
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In light of this, such problem is addressed by proposing the probabilistic aspect mining model (PAMM) for identifying the aspects/topics relating to class labels. ...
Reviews of medication from patients are numerous on the internet. This review provides a brief overview of approaches to aspect mining as they relate to drug discovery. ...
Conclusion The proposed probabilistic aspect mining model (PAMM) which is used for mining of aspects relating to specified labels or groupings of drug reviews is more accurate comparing with other supervised ...
doi:10.21275/v4i11.nov151059
fatcat:v6rxxlde7nfora4cl6735fyt74
A Review on Different Opinion and Aspect Mining Techniques
2016
International Journal of Computer Applications
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With the rising popularity of internet, online drug reviews have been proved to be extremely helpful for patients suffering from chronic diseases. ...
Opinion mining or aspect mining involves the extraction of useful information (e.g. positive or negative sentiments of a product) from a large quantity of text opinions or reviews given by Internet users ...
PAMM Probabilistic Aspect Mining Model (PAMM) [11] is a probabilistic model for finding the aspects which are correlated to class labels from the drug reviews given by the users.Reviews are generated ...
doi:10.5120/ijca2016908127
fatcat:2jxs6ieningr3nd4kj6lak4qwq
Automatic integration of drug indications from multiple health resources
2010
Proceedings of the ACM international conference on Health informatics - IHI '10
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This paper researches on a program for analysing the patient's medical history using the detection of PAMM (Probabilistic Aspect Mining Model) Algorithm. ...
There are lots of major issues in assessing the safety of the drugs. One of the major issues is Automatic Integration of Drug Indications. ...
Algorithm: Probabilistic Aspect Mining Model (PAMM) 1: Compute the empirical mean for {(xn)}N n=1 (i.e. μ). 2: Center the data by xn ← (xn − μ) for n = 1, . . . ...
doi:10.1145/1882992.1883096
dblp:conf/ihi/NeveolL10
fatcat:gscv3jao4jd5rie4cucqyhko54
An Effective Stratified K-Fold Algorithm with Logistic Regression for Drug Feedback Data
2020
International journal of recent technology and engineering
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Generally, drug review contains details of drug name, usage, ratings and comments by the patients. ...
However, these reviews are not clean, and there is a need to improve the cleanness of the review so that they can be benefited for both pharmacists and patients. ...
PAMM for mining aspects relating to specified labels or groupings of drug reviews are used in [5] . ...
doi:10.35940/ijrte.f8166.038620
fatcat:sfzydbkvzvcfpabkvhrabumkwm
Classification of drugs reviews using W-LRSVM model
2015
2015 Annual IEEE India Conference (INDICON)
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A model is designed by proposing an algorithm which crawls information from the web to analyze reviews of drugs. Reviews were crawled for five different drugs using the algorithm. ...
Opinion mining provided less opportunity to discuss their experiences about drugs so reviewing about it was difficult. ...
RELATED WORK Probabilistic Aspect Based Mining Model (PAMM) deals with aspects related to drugs. PAMM is a supervised algorithm which finds the aspects correlated to one class labels only. ...
doi:10.1109/indicon.2015.7443425
fatcat:e3n47udzizbolly3qm7kpjgyk4
Map Reduce Framework Driven Apriori Algorithm Base Model of Opinion Mining for drug Review
2016
International Journal Of Engineering And Computer Science
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The proposed work is extension to our previous work [1] on opinion mining of drug reviews. The proposed model is tested on WebMD blog reviews which shown the good results. ...
Applying opinion mining concepts on map reduce frame work for drug review can lead to a useful platform to extract and answer needs of research community. ...
paper for map reduce base a priory algorithm driven opinion mining of drug reviews. ...
doi:10.18535/ijecs/v5i11.17
fatcat:ihey5jjvpfaifc3vfxq5sb7s74
Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey
[article]
2018
arXiv
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Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents. ...
Researchers have proposed various models based on the LDA in topic modeling. According to previous work, this paper can be very useful and valuable for introducing LDA approaches in topic modeling. ...
Acknowledgements This article has been awarded by the National Natural Science Foundation of China (61170035, 61272420, 81674099, 61502233), the Fundamental Research Fund for the Central Universities ( ...
arXiv:1711.04305v2
fatcat:jzsx6owjyjfo3gkbohrc2ggkzq
A Review of Feature Selection Algorithms in Sentiment Analysis for Drug Reviews
2021
International Journal of Advanced Computer Science and Applications
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This review paper has also identified previous studies that applied metaheuristics algorithm as a feature selection algorithm in the medical domain, especially studies that used drug review data. ...
Data sources in the medical domain may exist in the form of clinical documents, nurse's letter, drug reviews, MedBlogs, and Slashdot interviews. ...
ACKNOWLEDGMENT The authors gratefully acknowledge Universiti Pertahanan Nasional Malaysia, and the Skim Geran Penyelidikan Jangka Pendek Fasa 1/2021 for supporting this research project through grant no ...
doi:10.14569/ijacsa.2021.0121217
fatcat:zjfk7mw36jbk3g22z2gxai5p3q
Topic Modeling: A Comprehensive Review
2018
EAI Endorsed Transactions on Scalable Information Systems
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Topic modelling is the new revolution in text mining. It is a statistical technique for revealing the underlying semantic structure in large collection of documents. ...
Quantitative evaluation of topic modeling techniques is also presented in detail for better understanding the concept of topic modeling. ...
Understanding more precisely which pathway are affected by drugs in specific cell types open up new possibilities for more targeted drugs or combination drug therapies. ...
doi:10.4108/eai.13-7-2018.159623
fatcat:lu6al57vp5aahbytyejhqrlzry
Patient opinion mining to analyze drugs satisfaction using supervised learning
2017
Journal of Applied Research and Technology
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This work aims to apply neural network based methods for opinion mining from social web in health care domain. We have extracted the reviews of two different drugs. ...
Experimental analysis is done to analyze the performance of classification methods on reviews of two different drugs. ...
There are also very few studies specifically on opinion mining in the drug domain. Na et al. (2012) proposed a rule-based system for polarity classification of drug reviews. ...
doi:10.1016/j.jart.2017.02.005
fatcat:3te5m6gp7rd6vdpitfkplc6ojq
Deep Learning Approaches for Big Data Analysis
2019
Proceeding of the Electrical Engineering Computer Science and Informatics
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Finally, we will show how we exploited deep learning method for the opinion mining and later used it to extract the product's aspects from the user textual review for recommendation systems. ...
We show effectiveness of the proposed model in terms of both aspect extraction and rating prediction performance. ...
Finally, we will show how we exploited deep learning method for the opinion mining and later used it to extract the product's aspects from the user textual review for recommendation systems. ...
doi:10.11591/eecsi.v6.2008
fatcat:gqvjrcios5bl3aendwrlxr5uxu
A Conceptual Data Modelling Framework for Context-Aware Text Classification
2020
International Journal of Advanced Computer Science and Applications
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The model is tested using drug review dataset obtained from UCI repository. The health conditions with their associated drug names were extracted from the reviews and sentiment scores were assigned. ...
"Why type questions" find their applications in emotion classification, brand analysis, drug review modeling, customer complaints classification etc. ...
PERFORMANCE EVALUATION The model is tested using drug review dataset. ...
doi:10.14569/ijacsa.2020.0111116
fatcat:stvglva6izfyfcie7xxwifgq6m
Transforming big data into computational models for personalized medicine and health care
2016
Dialogues in Clinical Neuroscience
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Due to the complexity and challenges inherent in studying medical information, it is not yet possible to create a comprehensive model capable of considering all the aspects of health care systems. ...
En raison de la complexité et des difficultés liées à l'etude des informations médicales, il n'est pas encore possible de créer un modèle complet prenant en compte tous les aspects des systèmes de santé ...
Acknowledgements: The authors would like to thank Craig Biwer and Samuel Habbo-Gavin for their valuable comments. ...
pmid:27757067
pmcid:PMC5067150
fatcat:x7ryh3zm4jfujhiinhediczyny
Asymmetric author-topic model for knowledge discovering of big data in toxicogenomics
2015
Frontiers in Pharmacology
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In this paper, we developed a generalized probabilistic topic model to analyze a toxicogenomics dataset that consists of a large number of gene expression data from the rat livers treated with drugs in ...
The analogy between text corpus and large-scale genomic data enables the application of text mining tools, like probabilistic topic models, to explore hidden patterns of genomic data and to the extension ...
Acknowledgments MC is grateful to the National Center for Toxicological Research (NCTR) of U. S. Food and Drug Administration (FDA) for internship opportunity through Oak Ridge Institute for Science ...
doi:10.3389/fphar.2015.00081
pmid:25941488
pmcid:PMC4403303
fatcat:eiij26abovfj3cquu35iust5ou
The application of text mining algorithms in summarizing trends in anti-epileptic drug research
[article]
2018
bioRxiv
pre-print
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A sentiment analysis model was created to score the abstracts for sentiment positivity or negativity. ...
The volume of studies published on anti-epileptic drugs (AED) has increased exponentially over the last two decades, making it an important area for the application of text mining based summarization algorithms ...
Modified LDA based Topic Modelling Latent Dirichlet Allocation (LDA) is a well-defined, unsupervised, generative, probabilistic method for modeling data and is frequently used in topic modeling (Blei ...
doi:10.1101/269308
fatcat:djs5rgojzjceznarzjbscvpk2u
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