Jesmin Nahar

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This paper investigates a number of computational intelligence techniques in the detection of heart disease. Particularly, comparison of six well known classifiers for the well used Cleveland data is performed. Further, this paper highlights the potential of an expert judgment based (i.e., medical knowledge driven) feature selection process (termed as MFS),(More)
Cancer is increasing the total number of unexpected deaths around the world. Until now, cancer research could not significantly contribute to a proper solution for the cancer patient, and as a result, the high death rate is uncontrolled. The present research aim is to extract the significant prevention factors for particular types of cancer. To find out the(More)
Microarray data classification is one of the most important emerging clinical applications in the medical community. Machine learning algorithms are most frequently used to complete this task. We selected one of the state-of-the-art kernel-based algorithms, the support vector machine (SVM), to classify microarray data. As a large number of kernels are(More)
Microarray analysis creates a clear scenario for the complete transcription profile of cells that facilitate drug and therapeutics development, disease diagnosis and enable us to take an in depth look at cell biology. One of the key challenges in microarray analysis, especially in cancerous gene expression profiles, is to identify genes or groups of genes(More)
The goal of this research is to develop a computer aided diagnostic (CAD) system that can detect breast cancer in the early stage by using microarray and image data. We verified the performance of six well known classification algorithms with various performance matrices. Although we do not suggest a unique classifier algorithm for a CAD system, we do(More)
This chapter is a review of data mining techniques used in medical research. It will cover the existing applications of these techniques in the identification of diseases, and also present the authors' research experiences in medical disease diagnosis and analysis. A computational diagnosis approach can have a significant impact on accurate diagnosis and(More)
Though an important preliminary process to diagnose cardiac abnormality, cardiac stress test is often inaccurate and involves costly follow-up procedures. Data mining based approaches have potentials to reduce the uncertainties in this respect. However, the exploration on such data mining approaches is still limited. Further, traditionally employed data(More)
The diagnosis of disease is difficult but critical task in medicine. Data mining is the process of extracting hidden interesting patterns from massive database. In the healthcare industry it plays a significant task for predicting the disease. Heart disease is a single largest cause of death in developed countries and one of the main contributors to disease(More)