An Optimized Intelligent Dermatologic Disease Classification Framework Based on IoT

2020 ◽  
pp. 131-151
Author(s):  
Shouvik Chakraborty ◽  
Sankhadeep Chatterjee ◽  
Kalyani Mali
Keyword(s):  
Disease Classification ◽  
Classification Framework ◽  
Dermatologic Disease

scholarly journals An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions

Computers ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 62 ◽  
Author(s):  
Nazia Hameed ◽  
Fozia Hameed ◽  
Antesar Shabut ◽  
Sehresh Khan ◽  
Silvia Cirstea ◽  
...  
Keyword(s):  
Classification Scheme ◽  
Skin Diseases ◽  
Research Work ◽  
Skin Lesions ◽  
Disease Classification ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Classification Framework ◽  
Computer Aided

Skin diseases cases are increasing on a daily basis and are difficult to handle due to the global imbalance between skin disease patients and dermatologists. Skin diseases are among the top 5 leading cause of the worldwide disease burden. To reduce this burden, computer-aided diagnosis systems (CAD) are highly demanded. Single disease classification is the major shortcoming in the existing work. Due to the similar characteristics of skin diseases, classification of multiple skin lesions is very challenging. This research work is an extension of our existing work where a novel classification scheme is proposed for multi-class classification. The proposed classification framework can classify an input skin image into one of the six non-overlapping classes i.e., healthy, acne, eczema, psoriasis, benign and malignant melanoma. The proposed classification framework constitutes four steps, i.e., pre-processing, segmentation, feature extraction and classification. Different image processing and machine learning techniques are used to accomplish each step. 10-fold cross-validation is utilized, and experiments are performed on 1800 images. An accuracy of 94.74% was achieved using Quadratic Support Vector Machine. The proposed classification scheme can help patients in the early classification of skin lesions.

A Frequent Pattern Based Time Series Classification Framework

2010 ◽  
Vol 32 (2) ◽  
pp. 261-266
Author(s):  
Li Wan ◽  
Jian-xin Liao ◽  
Xiao-min Zhu ◽  
Ping Ni
Keyword(s):  
Time Series ◽  
Frequent Pattern ◽  
Time Series Classification ◽  
Classification Framework

Revisiting the Utsira Saline Aquifer CO2 Storage Resources Using the SRMS Classification Framework

2019 ◽  
Author(s):  
Sylvain Thibeau ◽  
Lesley Seldon ◽  
Franco Masserano ◽  
Jacobo Canal Vila ◽  
Philip Ringrose
Keyword(s):  
Co2 Storage ◽  
Saline Aquifer ◽  
Classification Framework

PUBLISHING PATTERNS IN SPECIALIST ACCOUNTING HISTORY JOURNALS IN THE ENGLISH LANGUAGE, 1996–1999

2000 ◽  
Vol 27 (2) ◽  
pp. 177-198 ◽  
Author(s):  
Garry D. Carnegie ◽  
Brad N. Potter
Keyword(s):  
Empirical Evidence ◽  
English Language ◽  
Time Span ◽  
International Accounting ◽  
Accounting History ◽  
Classification Framework ◽  
International Publishing ◽  
The Subject

While accounting researchers have explored international publishing patterns in the accounting literature generally, little is known about recent contributions to the specialist international accounting history journals. Specifically, this study surveys publishing patterns in the three specialist, internationally refereed, accounting history journals in the English language during the period 1996 to 1999. The survey covers 149 contributions in total and provides empirical evidence on the location of their authors, the subject country or region in each investigation, and the time span of each study. It also classifies the literature examined based on the literature classification framework provided by Carnegie and Napier [1996].

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