"CANFIS—a computer aided diagnostic tool for cancer detection"
written by Latha Parthiban, R. Subramanian,
published by Journal of Biomedical Science and Engineering, Vol.2 No.5, 2009
has been cited by the following article(s):
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[1] Comparing Existing Methods for Predicting the Detection of Possibilities of Blood Cancer by Analyzing Health Data
[2] Detection and Diagnosis of Tumor Regions in Thyroid Images using CANFIS Classifier
[3] Automated Detection of Breast Cancer Using Artificial Neural Networks and Fuzzy Logic
[4] Detection and Diagnosis of Tumor Regions in Thyroid Images using CANFIS Classifier.
Applied Medical Informatics, 2017
[5] Prediction of Early Recurrence of Liver Cancer by a Novel Discrete Bayes Decision Rule for Personalized Medicine
BioMed Research International, 2016
[6] New methodologies for efficient computer aided malignancy diagnosis in digital mammograms
[7] Automated analysis on enhancing the diagnostic relevance of tuberculosis images using image processing and artificial intelligence
[8] Prediction of permeability in a tight gas reservoir by using three soft computing approaches: A comparative study
Journal of Natural Gas Science and Engineering, Elsevier, 2014
[9] Evaluación del desempe?o de dos modelos de redes neuronales artificiales para clasificar flores de Petunia spp con base en color.
[10] Malignancy detection in mammogram using gray level gradient buffering method
[11] A novel approach in malignancy detection of computer aided diagnosis
American Journal of Applied Sciences, 2012
[12] A Novel Approach in Malignancy Detection of Computer Aided Diagnosis.
American Journal of Applied Sciences, 2012, 2012
[13] Computer Aided Diagnosis using Alarm Pixel Generation and Region Growing Method
Digital Image Processing?, 2012
[14] Computer Aided Diagnosis of Malignancy in Mammograms
European Journal of Scientific Research, 2012, 2012