Histopathologcial and clonal study of combined lobular and ductal carcinoma of the breast.

Lobular carcinoma in situ (LCIS) clinically constitutes a risk factor for the subsequent development of either invasive lobular carcinoma (ILC) or invasive ductal carcinoma (IDC). In order to approach the possibility of this common precursor of both ILC and IDC, we investigated combined lobular and ductal carcinomas. Thirty-two cases of lobular carcinoma were picked up out of 773 cases of operated breast carcinomas.

Serum cytokine profiles in patients with prostate carcinoma.

It has been suggested that various cytokines are associated with the pathophysiology of prostate carcinoma (Pca). We profiled ten cytokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IFN-γ and TNF-α) in the serum levels of 11 patients with organ-confined Pca, 15 with advanced Pca without cachexia, 8 with advanced Pca with cachexia (cachexia group) and 5 healthy males as controls. Cytokines were measured using a highly sensitive fluorescence microsphere system.

Template learning of cellular neural network using genetic programming.

A new learning algorithm for space invariant Uncoupled Cellular Neural Network is introduced. Learning is formulated as an optimization problem. Genetic Programming has been selected for creating new knowledge because they allow the system to find new rules both near to good ones and far from them, looking for unknown good control actions.

Rough sets and genetic algorithms in learning cellular neural networks cloning template for decision making system.

We purpose to find a new beneficial method for accelerating the Decision-Making and classifier support applied on imprecise data. This acceleration can be done by integration between Rough Sets theory, which gives us the minimal set of decision rules, and the Cellular Neural Networks. Our method depends on Genetic Algorithms for designing the cloning template for more accuracy.

Decision making using hybrid rough sets and neural networks.

A methodology for using rough sets theory for preference modeling in decision problem is presented in this paper. We will introduce a new method where neural network systems and rough sets theory are completely integrated into a hybrid system and are used cooperatively for decision and classification support. At the first glance, the two methods we discuss have not much in common.

Medical diagnostic system using Fuzzy Coloured Petri Nets under uncertainty.

We propose a medical diagnostic system using Fuzzy Coloured Petri Nets (FCPN) in this paper. For complex real-world knowledge Fuzzy Petri Net (FPN) models have been proposed to perform fuzzy reasoning automatically. However, in the Petri Net we have to represent all kinds of processes by separate subnets even though the process has the same behavior of other one.

Extraction of fuzzy rules using neural networks with structure level adaptation--verification to the diagnosis of hepatobiliary disorders.

This paper presents the reasoning and learning method for fuzzy rules using structure level adaptation of neural networks. In a usual neural network mechanism, we can observe some behaviors during the learning process. Based on such behaviors of neuron activity, we can generate or annihilate the specified neurons respectively in hidden layer to achieve an overall good system.

Extraction of fuzzy rules using neural networks with structure level adaptation and its application to diagnosis for hepatobiliary disorders.

First, this paper presents the reasoning and the learning method for fuzzy rules using structure level adaptation of neural networks. In a usual neural network's mechanism, during learning process of rules, we can observe the following two behaviors: Case 1: If a neural network does not have enough neurons to be satisfied to infer, then the input weight vector will have a tendency to fluctuate greatly, even after a certain long period the learning process. In this case, the network needs to generate a new neuron as its parent's attribute is inherited.

Radiation therapy alone in the treatment of carcinoma of the uterine cervix: review of experience at Tokyo Women's Medical College (1969-1983).

Three hundred thirteen patients presented with squamous cell carcinoma of the uterine cervix at Tokyo Women's Medical College from 1969 to 1983. The results are presented here. All of the patients were treated by radiotherapy with curative intent with a combination of intracavitary cesium by low-dose rate, using T.

[Reliability and limitation of various diagnostic methods including nuclear medicine in myocardial disease (author's transl)].

Electrocardiography (ECG), echocardiography, nuclear method, cardiac catheterization, left ventriculography (LVG) and endomyocardial biopsy (biopsy) were performed in 40 cases of cardiomyopathy (CM), 9 of endocardial fibroelastosis (EFE) and 19 of specific heart muscle disease (SHMD), and the usefulness and limitation of each method was comparatively estimated. In CM, various methods including biopsy were performed. The 40 patients were classified into 3 groups, i.