The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Cancer diagnosis and treatment has a great significance due to the prevalent episodes of the diseases, high death rate and reappearance after treatment. On the world scale, cancer stands in the fifth position which causes death. Among the various cancers, liver cancer stands in the third position. Liver cancer is generally diagnosed by three different test like blood test, image test and biopsy. To...
The nucleotide sequence of biological databases is growing long terms of quantity, memory and complexity, managing these databases is becoming very complex. In this paper focuses Hidden Markov Model (HMM), has increased on the Pattern recognition domain primarily because of its strong mathematical basis and the ability to adapt to unknown of nucleotide sequence of normal and cancer affected liver...
Analysis of medical data sets can reveal important information, especially data coming from patients with cancer. That can be improved by use of data mining. However, to obtain coherent results coming from data mining, the correct selection of more semantic features should occur but, usually, that does not happen. Therefore, this work presents a proposal of automatic and semantic pre — selection of...
Multidisciplinary approach to treatment planning of brain tumors is a worldwide increasingly practice, this approach is achieved using multidisciplinary team meetings (MDTM) to discuss cases. Studies have shown two main barriers to maximizing the efficiency of the MDTM: lack of information and inadequate presentation of available data to the team members. These difficulties is the reason for design...
The gradual increase of cancer cases worldwide has been posing a need on the use of computing resources to accurately retrieve the information recorded in databases. One can highlight the retrieved information importance from a specialist in order to better evaluate pathological response and predict the cancer patient prognosis. This paper presents a way to represent knowledge of cancer registries...
Surface Enhanced Raman Spectroscopy (SERS) is a trace amount substance detecting technique developing quickly in recent years. In this paper, the saliva SERS spectrum of 59 lung cancer patients and 18 normal people were measured, and analyzed with data mining technology and the traditional statistical classification methods. The data were established by the Support Vector Machine (SVM), Random Forests...
Primary tumor is a neoplasm which in clinical parlance is regarded as malignant, arising in one site and capable of giving rise to metastatic tumors. Primary tumor disease is a major health problem in today's time. This paper aims at analyzing various data mining techniques for primary tumor prediction. The observations reveal that the hybrid approach of any three classifiers using Vote ensemble technique...
The development of data mining applications such as classification and clustering has shown the need for machine learning algorithms to be applied to large scale data. Cancer classification has improved over the past 20 years; there has been no general approach for identifying new cancer classes or for assigning tumors to known classes (class prediction). Most proposed cancer classification methods...
In this study we argue that the traditional approach of evaluating the information quality of an anonymized (or otherwise modified) dataset is questionable. We propose a novel and simple approach to evaluate the information quality of a modified dataset, and thereby the quality of techniques that modify data. We carry out experiments on eleven datasets and the empirical results strongly support our...
The multi factorial, chronic, severe diseases like diabetes and cancer have complex relationship. When the glucose level of the body goes to abnormal level, it will lead to Blindness, Heart disease, Kidney failure and also Cancer. Epidemiological studies have proved that several cancer types are possible in patients having diabetes. Many researchers proposed methods to diagnose diabetes and cancer...
With the huge growth in the volume of data today, there is an enhanced need to extract meaningful information from the data. Data mining contributes towards this and finds its application across various diverse domains such as in information technology, retail, stock markets, banking, and healthcare among others. The increase in population coupled with the growth in diseases has necessitated the inclusion...
Clustering is an effective machine learning method for classification and decision making. This paper builds a system model for loan management and incorporates the information clustering algorithm into this system. This clustering algorithm describes the cluster memberships with a non-parametric mutual information estimate between cluster assignment and data distribution. It can improve the classification...
Lung cancer is, one of the groups of malignant diseases affecting the Lung and associated organs. Pre-diagnosis is an important stage of identifying the target group of persons who can undergo diagnosis stage. In this study, a model is proposed based on ensemble of classifiers for prediction of lung cancer based on symptoms and risk factors. Data mining approach is adopted here, to develop model for...
The five-year survival rate of liver cancer is low, 14% according to the Surveillance, Epidemiology, and End Results (SEER) Program database of the National Cancer Institute from 2003 to 2007 [3]. Since in the early stages of liver cancer, patients usually do not show signs or symptoms, improving early diagnosis is essential in order to reduce morbidity and mortality rates.
The aim of this paper is to introduce procedure capable of compressing the representation of causal graphs, removing the redundant information introduced. In previous works we have presented several algorithms to extract causal information from text documents by means of a semi-automatic process. As result we obtained a causal graph connecting concepts related to a given topic.
Since microarray data have gene data consisting of large amounts of data, to improve the performance of cancer classification, features of useful data should be extracted. The present paper presents a method of classifying lymphoma cancers by extracting 20 data each from 4026 lymphoma data out of microarray data through a t-test and Euclidean distances among filtering methods using the NEWFM (Neural...
The task of semi-supervised outlier detection is to find the instances that are exceptional from other data with the use of some labeled examples. In many applications such as fraud detection and intrusion detection, this issue becomes important. Most existing techniques are unsupervised and the semi-supervised approaches use both negative and positive instances to detect outliers. However, in many...
Radiation therapy is used to treat cancer patients around the world. High quality treatment plans maximally radiate the targets while minimally radiating healthy organs at risk. In order to judge plan quality and safety, segmentations of the targets and organs at risk are created, and the amount of radiation that will be delivered to each structure is estimated prior to treatment. If the targets or...
Early diagnosis is an important aspect of successful treatment for breast cancer. Mammogram is the most reliable imaging technique available. It is a challenging task for radiologists to detect the abnormalities in the mammograms. Computing helps the radiologists in diagnosing the abnormalities in the mammogram. Computer Aided Diagnosis System involves computerized biomedical image analysis to classify...
Cancer prognosis prediction improves the quality of treatment and increases the survivability of the patients. Conventional methods of cancer prediction deal with single class by limiting the prognosis prediction to one response variable. The SEER Public Use cancer database has more prominent variables that support better prediction approach. The objective of this paper is to find the prominent labels...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.