Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Khanna H. Nehemiah"'
Publikováno v:
Journal of Computing and Information Technology, Vol 24, Iss 1, Pp 65-78 (2016)
Knowledge mined from clinical data can be used for medical diagnosis and prognosis. By improving the quality of knowledge base, the efficiency of prediction of a knowledge-based system can be enhanced. Designing accurate and precise clinical decision
Externí odkaz:
https://doaj.org/article/6e1ad4807af545a68d90c85c12aca6c4
Publikováno v:
Informatics in Medicine Unlocked, Vol 2, Iss , Pp 1-11 (2016)
Data mining techniques play a major role in developing computer aided diagnosis systems and expert systems that will aid a physician in clinical decision making. In this work, a classifier that combines the relative merits of fuzzy sets and extreme l
Externí odkaz:
https://doaj.org/article/be334b747e8546989e1fdc8cdb7e3d61
Autor:
R. Betshrine Rachel, Khanna H. Nehemiah, C.S. Marishanjunath, Rebecca Mercy Victoria Manoharan
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 44:5633-5646
A Computer Aided Diagnosis (CAD) framework to diagnose Pulmonary Edema (PE) and covid-19 from the chest Computed Tomography (CT) slices were developed and implemented in this work. The lung tissues have been segmented using Otsu’s thresholding meth
Publikováno v:
International Journal of Swarm Intelligence Research. 13:1-22
A new classification framework for a Clinical Decision Support System, utilizing a Genetic algorithm and an Artificial Flora Optimized Neural Network is presented in this paper. GAFON is an artificial neural network whose topology is optimized with G
Publikováno v:
International Journal of Operations Research and Information Systems. 11:62-85
Artificial neural networks (ANN) are widely used for classification, and the training algorithm commonly used is the backpropagation (BP) algorithm. The major bottleneck faced in the backpropagation neural network training is in fixing the appropriat
Artificial neural networks (ANN) are widely used for classification, and the training algorithm commonly used is the backpropagation (BP) algorithm. The major bottleneck faced in the backpropagation neural network training is in fixing the appropriat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00d604ae10d179a50d598c1799432017
https://doi.org/10.4018/978-1-6684-2408-7.ch009
https://doi.org/10.4018/978-1-6684-2408-7.ch009
Publikováno v:
Informatics in Medicine Unlocked, Vol 2, Iss, Pp 1-11 (2016)
Data mining techniques play a major role in developing computer aided diagnosis systems and expert systems that will aid a physician in clinical decision making. In this work, a classifier that combines the relative merits of fuzzy sets and extreme l
Publikováno v:
Applied clinical informatics. 7(1)
SummaryClinical time-series data acquired from electronic health records (EHR) are liable to temporal complexities such as irregular observations, missing values and time constrained attributes that make the knowledge discovery process challenging.Th