P. Wilding, M.A. Morgan, A.E. Grygotis, M.A. Sho#ner, and E.F. Rosato. Application of backpropagation neural networks to diagnosis of breast and ovarian cancer. Cancer Letter, 77:145--153, 1994. Home/Search Document Not in Database Summary Related Articles Check |
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An Evolutionary Artificial Neural Networks Approach for Breast.. - Abbass (2002) (1 citation) (Correct)
....Keywords Pareto optimization, di#erential evolution, artificial neural networks, breast cancer. 1 Introduction The economic and social values of Breast Cancer Diagnosis (BCD) are very high. As a result, the problem has attracted many researchers in the area of computational intelligence recently [6, 8, 10, 22, 26, 32, 33, 34]. Because of the importance of achieving highly accurate classification, Artificial Neural Networks (ANNs) are among the most common methods for BCD. Research in the area of using ANNs for medical purposes more specifically BCD [6, 8, 10, 22, 26, 32, 34] has been at the center of attention ....
....intelligence recently [6, 8, 10, 22, 26, 32, 33, 34] Because of the importance of achieving highly accurate classification, Artificial Neural Networks (ANNs) are among the most common methods for BCD. Research in the area of using ANNs for medical purposes more specifically BCD [6, 8, 10, 22, 26, 32, 34] has been at the center of attention for several years. Unfortunately, to our present knowledge, none of this type of research was able to enter the clinic either in terms of routine use or to replace the radiologist. This could be ascribed to a number of factors. The first problem was the ....
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P. Wilding, M.A. Morgan, A.E. Grygotis, M.A. Sho#ner, and E.F. Rosato. Application of backpropagation neural networks to diagnosis of breast and ovarian cancer. Cancer Letter, 77:145--153, 1994.
Intelligent Data Analysis in Medicine - Lavrac, Keravnou, Zupan (2000) (1 citation) (Correct)
....often have equal or superior predictive accuracy when compared to symbolic learners or statistical approaches [64, 154] They have been extensively used to model medical data. Example applications areas include survival analysis [98] clinical medicine [10] pathology and laboratory medicine [7], molecular sequence analysis [173] pneumonia risk assessment [21] and prostate cancer sur46 vival [65] There are fewer applications where rules were extracted from neural networks: an example of such data analysis is finding rules for breast cancer diagnosis [145] Di#erent types of neural ....
Astion, M.L. and Wielding, P., "The application of backpropagation neural networks to problems in pathology and laboratory medicine," Arch Pathol Lab Med, 116: 995--1001 (1992).
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....This paper describes ongoing work investigating machine learning (ML) techniques to support computer based oral cancer screening in primary and secondary healthcare. The studies described here were partly encouraged by other successful applications of machine learning in cancer diagnosis [8, 11, 17, 20, 21]. Until forty years ago, the incidence of oral cancer was continuing to decline but it is now rising in the UK and in other industrialised countries in Europe and North America. Approximately 2,000 cases of oral cancer are newly diagnosed in England and Wales each year, with an incidence of 4.5 ....
Wilding, P., Morgan, M.A., Grygotis, A.E., Shoffner, M.A., Rosato, E.F.: Application of back propagation neural networks to diagnosis of breast and ovarian cancer. Cancer Lett 74 (1994) 143-153.
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....fuzzy systems, seems to provide a solution to the above situation and constitutes a new emerging field in Diagnostic Cytology. Pattern recognition, data base search, knowledge extraction and decision making, are some of the most important applications of neural networks in the field of Cytology [1, 2, 8, 20]. Up to now neural networks have been successfully applied for the mass screening of Gynaecological Cytology samples [16] Gastric Cytology has not reached wide acceptance in the investigation of gastric lesions because of the difficulties in the discrimination of benign lesions with severe ....
M. L. Astion and P. Wilding, "The Application of Back Propagation Neural Networks to Problems in Pathology and Laboratory Medicine," Arch. Pathol. Lab. Med., Vol. 116, pp. 995--1001, 1992.
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P. Wilding, M.A Morgan, A.E. Grygotis, M.A. Shoffner, E.F. Rosato, "Application of Backpropagation Neural Networks to Diagnosis of Breast and Ovarian Cancer," Cancer Lett., vol. 77, no. 2-3, pp. 145-153, Mar. 1994.
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Astion ML, Wilding P. The application of backpropagation neural networks to problems in pathology and laboratory medicine. Arch Pathol Lab Med. 1992; 116:995-1001.
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Astion, M. L. & Wilding, P. 1992. 'The application of backpropagation neural networks to problems in pathology and laboratory medicine', Archives of Pathology and Laboratory Medicine vol. 116, p.995 -- 1001.
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Wilding P, Morgan MA, Grygotis AE, Shoffner MA, Rosato EF. Application of backpropagation neural networks to diagnosis of breast and ovarian cancer. Cancer Lett. 1994;77:145-53.
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