Earticle

초록

영어

In today’s word skin diseases and lesions have become one among the most common diseases that people suffer across various age groups. Typical skin illnesses that people suffer throughout the world and more particularly in developing countries are Bacterial Skin infections, Fungal skin infection, Eczema and Scabies. Identification of the influential clinical symptoms that help in the diagnosis of these illnesses in early phase of the illness would aid in designing effective public health management. Keeping this as our main objective, this paper describes the two predictive models for our multiclass classification problem. The models are developed using popular soft computing techniques namely Artificial Neural Network and Support Vector Machine. These two approaches are applied on the multi class classification dataset and some comparative inferences are generated using F-scores.

목차

Abstract
 1. Introduction
 2. Literature Review
 3. Data Description-Data Preparation
 4. Soft Computing Techniques
  4.1 Artificial Neural Network (ANN):
  4.2. Support Vector Machine (SVM):
 5. Experimental Setup and Implementation Process
 6. Results and Discussion
 7. Conclusion
 References

키워드

저자

• Krupal S. Parikh [ Department of Applied Sciences & Humanities, G. H. Patel College of Engineering and Technology, Gujarat Technological University, Gujarat State, India ]
• Trupti P. Shah [ Department of Applied Mathematics, Faculty of Technology & Engineering, The M. S. University of Baroda, Vadodara, Gujarat State, India ]
• RahulKrishna Kota [ Department of Skin and VD,Shree krishna Hospital,Pramukh Swami Medical College, Karamsad, Anand, Gujarat, India ]
• Rita Vora [ Department of Skin and VD,Shree krishna Hospital,Pramukh Swami Medical College, Karamsad, Anand, Gujarat, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605