Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset
نویسندگان
چکیده
Data Mining is an assortment of effective tool set to perform the statistical analysis on an immense dataset and to retrieve the valuable information from the dataset. In this work we have carried out an analytical survey on predictive data mining approaches on clinical dataset. The clinical dataset processing is one of the effective and most sensitive area which is studied under an expert environment. The present paper discusses KDD, data mining with reference to clinical expert system analysis, different applications and the approaches that can be used for the predictive data mining in same area. The scope of this paper is confined to the prediction of a person disease, based on symptoms dataset. The strength of data mining approaches in diverse clinical applications is also analyzed.
منابع مشابه
Predicting Implantation Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection Using Data Mining Techniques
Objective The main purpose of this article is to choose the best predictive model for IVF/ICSI classification and to calculate the probability of IVF/ICSI success for each couple using Artificial intelligence. Also, we aimed to find the most effective factors for prediction of ART success in infertile couples. MaterialsAndMethods In this cross-sectional study, the data of 486 patients are colle...
متن کاملAccuracy evaluation of different statistical and geostatistical censored data imputation approaches (Case study: Sari Gunay gold deposit)
Most of the geochemical datasets include missing data with different portions and this may cause a significant problem in geostatistical modeling or multivariate analysis of the data. Therefore, it is common to impute the missing data in most of geochemical studies. In this study, three approaches called half detection (HD), multiple imputation (MI), and the cosimulation based on Markov model 2...
متن کاملExtracting Predictor Variables to Construct Breast Cancer Survivability Model with Class Imbalance Problem
Application of data mining methods as a decision support system has a great benefit to predict survival of new patients. It also has a great potential for health researchers to investigate the relationship between risk factors and cancer survival. But due to the imbalanced nature of datasets associated with breast cancer survival, the accuracy of survival prognosis models is a challenging issue...
متن کاملPredicting Type2 Diabetes Using Data Mining Algorithms
Background and purpose: Today, information systems and databases are widely used and in order to achieve higher accuracy and speed in making diagnosis, preventing the diseases, and choosing treatments they should be merged with traditional methods. This study aimed at presenting an accurate system for diagnosis of diabetes using data mining and a heuristic method combining neural network and pa...
متن کاملImproving Fraud and Abuse Detection in General Physician Claims: A Data Mining Study
Background We aimed to identify the indicators of healthcare fraud and abuse in general physicians’ drug prescription claims, and to identify a subset of general physicians that were more likely to have committed fraud and abuse. Methods We applied data mining approach to a major health insurance organization dataset of private sector general physicians’ prescription claims. It involved 5 ste...
متن کامل