Breast cancer is a major health burden worldwide being a major cause of death amongst women. In this paper, Fuzzy Inference Systems (FIS) are developed for the evaluation of breast cancer risk using Mamdani-type and Sugeno-type models. The paper outlines the basic difference between Mamdani-type FIS and Sugeno-type FIS. The results demonstrated the performance comparison of the two systems and the advantages of using Sugeno- type over Mamdani-type
This paper presents a Hidden Markov Model (HMM) based fuzzy model for breast cancer recognition and ...
Breast cancer is one of the most frequent occurring cancers in women throughout the world including ...
AbstractIt has been often demonstrated that clinicians exhibit both inter-expert and intra-expert va...
Every year thousands of human mortality from cancer is due to limitation of medical sources and unab...
A breast cancer risk assessment based on fuzzy set theory and fuzzy logic is proposed in this paper....
Cancer is the leading life-threatening disease for people in today's world. Although cancer formatio...
Objetivo: Comparar a capacidade de predição de estados dos receptores hormonais do modelo de lógica...
Breast cancer is an important medical problem, especially for women, computer-aided medical diagnosi...
It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variabilit...
The statistical estimation of the cancer research center shows that approximate 23 million new cases...
Breast cancer is currently one of the main causes of death and tumoral diseases in women. Even if ea...
Lack of information, imprecision, contradictory nature are common facts in medicine. Generally, the...
AbstractIn this paper, we present an agent-based system for distributed risk assessment of breast ca...
Breast cancer is currently one of the main causes of death and tumoral diseases in women. Even if ea...
A novel supervised machine learning algorithm that improves the 1993 Sugeno-Yasukawa (SY) modelling ...
This paper presents a Hidden Markov Model (HMM) based fuzzy model for breast cancer recognition and ...
Breast cancer is one of the most frequent occurring cancers in women throughout the world including ...
AbstractIt has been often demonstrated that clinicians exhibit both inter-expert and intra-expert va...
Every year thousands of human mortality from cancer is due to limitation of medical sources and unab...
A breast cancer risk assessment based on fuzzy set theory and fuzzy logic is proposed in this paper....
Cancer is the leading life-threatening disease for people in today's world. Although cancer formatio...
Objetivo: Comparar a capacidade de predição de estados dos receptores hormonais do modelo de lógica...
Breast cancer is an important medical problem, especially for women, computer-aided medical diagnosi...
It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variabilit...
The statistical estimation of the cancer research center shows that approximate 23 million new cases...
Breast cancer is currently one of the main causes of death and tumoral diseases in women. Even if ea...
Lack of information, imprecision, contradictory nature are common facts in medicine. Generally, the...
AbstractIn this paper, we present an agent-based system for distributed risk assessment of breast ca...
Breast cancer is currently one of the main causes of death and tumoral diseases in women. Even if ea...
A novel supervised machine learning algorithm that improves the 1993 Sugeno-Yasukawa (SY) modelling ...
This paper presents a Hidden Markov Model (HMM) based fuzzy model for breast cancer recognition and ...
Breast cancer is one of the most frequent occurring cancers in women throughout the world including ...
AbstractIt has been often demonstrated that clinicians exhibit both inter-expert and intra-expert va...