Bilgiç, Burcu

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/7812
Name Variants
Bilgic Ucak, Burcu
Burcu, Bilgiç
Bilgic, Burcu
B., Burcu
B.,Burcu
B., Bilgic
B.,Bilgic
Bilgic,B.
B.,Bilgiç
Burcu, Bilgic
Bilgiç, Burcu
Bilgiç,B.
Job Title
Araştırma Görevlisi
Email Address
bilgic.burcu@atilim.edu.tr
Main Affiliation
Department of Electrical & Electronics Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
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QUALITY EDUCATION4
QUALITY EDUCATION
0
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GENDER EQUALITY5
GENDER EQUALITY
0
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
1
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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CLIMATE ACTION13
CLIMATE ACTION
0
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LIFE BELOW WATER14
LIFE BELOW WATER
0
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LIFE ON LAND15
LIFE ON LAND
0
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

4

Articles

2

Views / Downloads

2/8

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

26

Scopus Citation Count

44

Patents

0

Projects

0

WoS Citations per Publication

6.50

Scopus Citations per Publication

11.00

Open Access Source

2

Supervised Theses

1

JournalCount
29th IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUN 09-11, 2021 -- ELECTR NETWORK1
Journal of Applied Statistics1
Sustainability1
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Type: Conference Object

Scholarly Output Search Results

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    Conference Object
    Citation - WoS: 3
    Citation - Scopus: 20
    Comparison of Breast Cancer and Skin Cancer Diagnoses Using Deep Learning Method
    (Ieee, 2021) Bilgic, Burcu
    Artificial intelligence applications are of great importance in the solution of cancer, which is one of the biggest health problems of our age. In this study, a study was conducted on deep learning methods that make life important in the early diagnosis of breast cancer and skin cancer, which are among the most common types of cancer worldwide. Breast cancer and skin cancer data were classified as benign and malignant by deep learning methods. While working with the deep learning method, the classification was made using the Convolutional Neural Network (CNN) algorithm. In this classification, the data are divided into benign cancer sets and malignant cancer sets. Finally, the data provided by the logistic regression method were analyzed and success charts were created and both types were compared. As a result, accuracy and loss graphs of both cancer types were formed. The aim of the study is to compare breast cancer and skin cancer with the deep learning method. And some breast cancer and skin cancer diagnoses are confused. In further studies, the basis of differentiating the diagnosis of these two types of cancer from each other was made in this study.