An improved medical image classification model using data mining techniques

2013 ◽  
Author(s):  
Satej Wagle ◽  
J. Alamelu Mangai ◽  
V. Santosh Kumar
Keyword(s):  
Data Mining ◽  
Image Classification ◽  
Medical Image ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Medical Image Classification ◽  
Using Data

scholarly journals Hybrid classification model to detect advanced intrusions using data mining techniques

2018 ◽  
Vol 7 (2.4) ◽  
pp. 10
Author(s):  
V Mala ◽  
K Meena
Keyword(s):  
Data Mining ◽  
Learning Algorithm ◽  
Detection System ◽  
Classification Model ◽  
Detection Methods ◽  
Data Mining Techniques ◽  
Detection Systems ◽  
Intruder Detection ◽  
Hybrid Classification ◽  
Using Data

Traditional signature based approach fails in detecting advanced malwares like stuxnet, flame, duqu etc. Signature based comparison and correlation are not up to the mark in detecting such attacks. Hence, there is crucial to detect these kinds of attacks as early as possible. In this research, a novel data mining based approach were applied to detect such attacks. The main innovation lies on Misuse signature detection systems based on supervised learning algorithm. In learning phase, labeled examples of network packets systems calls are (gave) provided, on or after which algorithm can learn about the attack which is fast and reliable to known. In order to detect advanced attacks, unsupervised learning methodologies were employed to detect the presence of zero day/ new attacks. The main objective is to review, different intruder detection methods. To study the role of Data Mining techniques used in intruder detection system. Hybrid –classification model is utilized to detect advanced attacks.

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

scholarly journals A Medical Image Classification Model Based on Adversarial Lesion Enhancement

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Bing Zhang ◽  
Xu Hu
Keyword(s):  
Image Classification ◽  
Medical Image ◽  
Medical Images ◽  
Learning Task ◽  
Classification Model ◽  
Lesion Area ◽  
Model Based ◽  
Modeling Process ◽  
Medical Image Classification ◽  
Diagnosis Model

With the development of Artificial Intelligence, the auxiliary diagnosis model based on deep learning can assist doctors to a certain extent. However, the latent information in medical images, such as lesion features, is ignored in most of the traditional methods. The extraction of this information is regarded as a learning task within the network in some recent researches, but it requires a large amount of fine-labeled data, which is undoubtedly expensive. In response to the problem above, this paper proposes an Adversarial Lesion Enhancement Neural Network for Medical Image Classification (ALENN), which is used to locate and enhance the lesion information in medical images only under weakly annotated data so as to improve the accuracy of the auxiliary diagnosis model. This method is a two-stage framework, including a structure-based lesion adversarial inpainting module and a lesion enhancement classification module. The first stage is used to repair the lesion area in the images while the second stage is used to locate the lesion area and use the lesion enhanced data during modeling process. In the end, we verified the effectiveness of our method on the MURA dataset, a musculoskeletal X-ray dataset released by Stanford University. Experimental results show that our method can not only locate the lesion area but also improve the effectiveness of the auxiliary diagnosis model.

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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