scholarly journals Data Mining in Cancer Diagnosis and Prediction: Review about Latest Ten Years

2020 ◽  
pp. 11-32
Author(s):  
Zahraa Naser Shah Weli
Keyword(s):  
Data Mining ◽  
Cancer Detection ◽  
Lower Cost ◽  
Medical Data ◽  
Medical Field ◽  
Clinical Prognosis ◽  
Cancer Prediction ◽  
Hidden Patterns ◽  
Vague Data

Data Mining [DM] has exceptional and prodigious potential for examining and analyzing the vague data of the medical domain. Where these data are used in clinical prognosis and diagnosis. Nevertheless, the unprocessed medical data are widely scattered, diverse in nature, and voluminous. These data should be accumulated in a sorted out structure. DM innovation and creativity give a customer a situated way to deal with new fashioned and hidden patterns in the data. The advantages of using DM in medical approach are unbounded and it has abundant applications, the most important: it leads to better medical treatment with a lower cost. Consequently, DM algorithms have the main usage in cancer detection and treatment through providing a learning  rich environment which can help to improve the quality of clinical decisions. Multi researches are published about the using of DM in different destinations in the medical field. This paper provides an elaborated study about utilization of DM in cancer prediction and classifying, in addition to the  main features and challenges in these researches are introduced in this paper for helping  apprentice and youthful scientists and showing for them the key principle issues that are still exist around there.

Knowledge Management in Hospitals

2005 ◽  
pp. 14-28 ◽  
Author(s):  
Kevin C. Desouza
Keyword(s):  
Knowledge Management ◽  
Process Model ◽  
Lower Cost ◽  
Quality Of Healthcare ◽  
Management Process ◽  
Healthcare Organizations ◽  
Medical Field

The medical field in recent years has been facing increasing pressures for lower cost and increased quality of healthcare. These two pressures are forcing dramatic changes throughout the industry. Managing knowledge in healthcare enterprises is hence crucial for optimal achievement of lowered cost of services with higher quality. The following chapter focuses on developing and fostering a knowledge management process model. We then look at key barriers for healthcare organizations to cross in order to fully manage knowledge.

scholarly journals Data Mining Technique Based Critical Disease Prediction in Medical Field

2020 ◽  
Author(s):  
Preetha J ◽  
Raju S ◽  
Abhishek Kumar ◽  
Sayyad Samee ◽  
Vengatesan R
Keyword(s):  
Data Mining ◽  
Field Data ◽  
Focal Point ◽  
Heterogeneous Data ◽  
Medical Data ◽  
Disease Prediction ◽  
Medical Field ◽  
Data Mining Technique ◽  
Research Papers ◽  
Medical Dataset

In the present days’ deaths because of some critical disease has become a significant issue in the medical field. Data mining is one of the significant territories of research that is famous in wellbeing associations. Data mining has a functioning job for finding new patterns and examples in the healthcare association which is valuable for every one of the gatherings related to this field. The medical dataset has heterogeneous data as numbers, content, and pictures that can be mined to convey an assortment of helpful data for the physicians. The examples picked up from the medical data can be helpful for the physicians to find diseases, foresee the survivability of the patients after disease, the seriousness of diseases and so forth. The focal point of this paper is to break down the utilization of data mining in medical space and a portion of the systems utilized in critical disease prediction. We have completely reviewed many research papers of data mining identified with some critical disease prediction.

Knowledge Management in Hospitals

2011 ◽  
pp. 208-221 ◽  
Author(s):  
Kevin C. Desouza
Keyword(s):  
Knowledge Management ◽  
Process Model ◽  
Lower Cost ◽  
Quality Of Healthcare ◽  
Management Process ◽  
Healthcare Organizations ◽  
Medical Field

The medical field in recent years has been facing increasing pressures for lower cost and increased quality of healthcare. These two pressures are forcing dramatic changes throughout the industry. Managing knowledge in healthcare enterprises is hence crucial for optimal achievement of lowered cost of services with higher quality. The following chapter focuses on developing and fostering a knowledge management process model. We then look at key barriers for healthcare organizations to cross in order to fully manage knowledge.

Knowledge Management in Hospitals

2011 ◽  
pp. 2191-2204
Author(s):  
Kevin C. Desouza
Keyword(s):  
Knowledge Management ◽  
Process Model ◽  
Lower Cost ◽  
Quality Of Healthcare ◽  
Management Process ◽  
Healthcare Organizations ◽  
Medical Field

The medical field in recent years has been facing increasing pressures for lower cost and increased quality of healthcare. These two pressures are forcing dramatic changes throughout the industry. Managing knowledge in healthcare enterprises is hence crucial for optimal achievement of lowered cost of services with higher quality. The following chapter focuses on developing and fostering a knowledge management process model. We then look at key barriers for healthcare organizations to cross in order to fully manage knowledge.

Using the Fuzzy Logic to Find Optimal Centers of Clusters of K-means

2016 ◽  
Vol 6 (6) ◽  
pp. 3068
Author(s):  
Wed Kadhim Oleiwi
Keyword(s):  
Data Mining ◽  
Fuzzy Logic ◽  
Heart Disease ◽  
Real World ◽  
Medical Diagnosis ◽  
Medical Data ◽  
World Health ◽  
Medical Field ◽  
Healthcare Data ◽  
Field Researcher

<p>Techniques of data mining that used in the medical diagnosis a number of diseases like cancer, diabetes, stroke, and heart disease. The great importance emerging fields for providing diagnosis and a profounder understanding of medical data, its coms from Data mining in medical field .researcher attempts to solve real world health problems in the prognosis and treatment of diseases, by using Healthcare data mining. In this research, the algorithm of k-means is used for grouping medical data, the problem of k-means is to find optimal centers of clusters so, and fuzzy logic is used to get optimal centers of clusters.</p>

Reducing the Feature Space Using Constraint-Governed Association Rule Mining

2017 ◽  
Vol 26 (1) ◽  
pp. 139-152
Author(s):  
◽  
M. Umme Salma
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Association Rule ◽  
Association Rule Mining ◽  
Medical Data ◽  
Cancer Surveillance ◽  
Feature Subset ◽  
Rule Mining ◽  
Data Set

AbstractRecent advancements in science and technology and advances in the medical field have paved the way for the accumulation of huge amount of medical data in the digital repositories, where they are stored for future endeavors. Mining medical data is the most challenging task as the data are subjected to many social concerns and ethical issues. Moreover, medical data are more illegible as they contain many missing and misleading values and may sometimes be faulty. Thus, pre-processing tasks in medical data mining are of great importance, and the main focus is on feature selection, because the quality of the input determines the quality of the resultant data mining process. This paper provides insight to develop a feature selection process, where a data set subjected to constraint-governed association rule mining and interestingness measures results in a small feature subset capable of producing better classification results. From the results of the experimental study, the feature subset was reduced to more than 50% by applying syntax-governed constraints and dimensionality-governed constraints, and this resulted in a high-quality result. This approach yielded about 98% of classification accuracy for the Breast Cancer Surveillance Consortium (BCSC) data set.

scholarly journals Using the Fuzzy Logic to Find Optimal Centers of Clusters of K-means

2016 ◽  
Vol 6 (6) ◽  
pp. 3068
Author(s):  
Wed Kadhim Oleiwi
Keyword(s):  
Data Mining ◽  
Fuzzy Logic ◽  
Heart Disease ◽  
Real World ◽  
Medical Diagnosis ◽  
Medical Data ◽  
World Health ◽  
Medical Field ◽  
Healthcare Data ◽  
Field Researcher

<p>Techniques of data mining that used in the medical diagnosis a number of diseases like cancer, diabetes, stroke, and heart disease. The great importance emerging fields for providing diagnosis and a profounder understanding of medical data, its coms from Data mining in medical field .researcher attempts to solve real world health problems in the prognosis and treatment of diseases, by using Healthcare data mining. In this research, the algorithm of k-means is used for grouping medical data, the problem of k-means is to find optimal centers of clusters so, and fuzzy logic is used to get optimal centers of clusters.</p>

Using Data Mining Techniques to Discover Patterns in an Airline's Flight Hours Assignments

2017 ◽  
Vol 13 (2) ◽  
pp. 45-62 ◽  
Author(s):  
Francisco Javier Villar Martín ◽  
Jose Luis Castillo Sequera ◽  
Miguel Angel Navarro Huerga
Keyword(s):  
Data Mining ◽  
Information System ◽  
Data Model ◽  
Free Software ◽  
Data Mining Techniques ◽  
Visualization Tools ◽  
Hidden Patterns ◽  
Using Data ◽  
Analyze Data

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.

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